Glassdoor gives you an inside look at what it&#x27;s like to work at HealthKart, including salaries, reviews, office photos, and more. This is the HealthKart company profile. All content is posted anonymously by employees working at HealthKart.

Working at HealthKart | Glassdoor

HealthKart | 130,766 followers on LinkedIn. Your partner for good health | HealthKart is a trusted house of brands with MuscleBlaze and HK Vitals being India’s no. 1 sports nutrition and online vitamin brands. HealthKart also offers a comprehensive range of products dedicated to the vegan ...

HealthKart | LinkedIn

HealthKart’s backstory is intriguing due to its association with the online pharmacy unicorn 1mg, previously known as HealthKartPlus. Both were set up by the parent company Bright Lifecare. While Maheshwari ran HealthKart, HealthKartPlus was headed by HealthKart’s Tandon, Gaurav Aggarwal ...

130+ Stores, 1K+ Brands, 40 Cities: How HealthKart Is Addressing ...

HealthKart offers fitness products and services to help consumers achieve their fitness goals. HealthKart also offers a comprehensive range of products dedicated to the vegan community, kids, and women for their wellness and fitness needs. The company started in 2011 and since then HealthKart ...

Healthkart - Crunchbase Company Profile & Funding

HealthKart offers health products online to help customers achieve fitness goals. Know about the Healthkart company, Healthkart founder, funding, revenue, and more.

HealthKart: How is it Offering Authentic Health Products Online?

HealthKart has 5 employees at their 1 location and $47 m in total funding,. See insights on HealthKart including office locations, competitors, revenue, financials, executives, subsidiaries and more at Craft.

HealthKart Company Profile - Office Locations, Competitors, Revenue, ...

HealthKart - Online store for health, sport, and nutritional supplements. Raised a total funding of $224M over 10 rounds from 20 investors. Valued at $370M. Founded by Sameer Maheshwari, Sameer Maheshwari and 1 other in the year 2011. HealthKart has 349 competitors.

HealthKart - Company Profile - Tracxn

The market is flooded with fake supplements or parallel imports that can cause harm to your body.

HealthKart: The platform to buy authentic products | Companies ...

Together, they decided to return to India and start a company in the healthcare space. ... A degree from Stanford or Harvard Business School would automatically win anybody tickets to a lucrative job. And it was no different for Sameer Maheshwari and Prashant Tandon. While the former is a Harvard graduate, the latter got his degree from Stanford. In fact, Maheshwari and Tandon quit their jobs to start, Healthkart...

Healthkart | How it Started

HealthKart is dedicated to providing everything that you will need in your journey towards a fitter you. From whey protein, vitamin c tablet, fat burners, mass gainers, weight gainers to herbal supplements like shatavari churna, to other bodybuilding supplements and nutritional supplements ...

HealthKart - India's #1 Authentic Online Supplement Store

HealthKart

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Table of Links Abstract and Introduction


Domain and Task
2.1. Data sources and complexity
2.2. Task definition


Related Work
3.1. Text mining and NLP research overview
3.2. Text mining and NLP in industry use
3.3. Text mining and NLP for procurement
3.4. Conclusion from literature review


Proposed Methodology
4.1. Domain knowledge
4.2. Content extraction
4.3. Lot zoning
4.4. Lot item detection
4.5. Lot parsing
4.6. XML parsing, data joining, and risk indices development


Experiment and Demonstration
5.1. Component evaluation
5.2. System demonstration


Discussion
6.1. The ‘industry’ focus of the project
6.2. Data heterogeneity, multilingual and multi-task nature
6.3. The dilemma of algorithmic choices
6.4. The cost of training data


Conclusion, Acknowledgements, and References 2. Domain and Task This work focuses on healthcare procurement, which has been rarely studied in the literature. The primary goal of the project is to develop a platform that allows the dynamic creation of a ‘supplier risk profile’ for each healthcare supplier. We envisage such a profile to consist of different ‘indices’ that evaluate different perspectives (e.g, capacity for supplying certain products, geographical coverage) of ‘risks’ for potential buyers to sign contracts with the supplier. This would enable questions such as ‘who are the suppliers able to supply this kind of medication’, ‘to what extent are they capable of supplying for this country’, or ‘are they able to supply such quantity’ to be easily answered. Such questions are often crucial for buyer decision making. However, the current procurement process relies on manually sifting through multiple lengthy documents to seek answers. This is a very resource consuming process. Understandably, an enabler of our primary goal would be a structured database of healthcare suppliers’ historical contract data. Thus the secondary goal of the project is to develop such a database and populate it with historical healthcare procurement data. While public procurement data is vastly available, as we shall explain in the following, there is a mixture of structured, semi-structured, and unstructured multilingual data that need to be mined and linked. Therefore, a major part of the project’s work is developing text mining and NLP solutions that automatically process large quantities of unstructured procurement data to mine information that can be used to populate the database. The goal of this article is therefore, to report the development of these text mining and NLP methods. 2.1. Data sources and complexity The project targets procurement data from the ‘Tenders Electronic Daily’ (TED) platform, which is used by the EU governments to publish their public procurement related projects. TED publishes over 460,000 calls for tenders and contract awards in 26 official European languages per year, for about 420 billion euro of value. Each tender may be divided into multiple ‘lots’, where a lot is the smallest contract unit. Each lot may contain multiple items that are required. As an example, tender notice ‘2019/S 180-437985’[1] lists 47 lots from an NHS (UK) tender, with their sizes ranging from 2 to over 30 items. If a tender secures successful bids, a ‘contract award’ (or multiple awards) will be made and recorded in TED for the tender. In the following, for the sake of explainability, we assume there is one award for each tender (however in practice, our methods are applied to all awards that are available for a tender). Note the lots offered in a tender and the contract awards form a ‘many-to-many’ relationship. Namely, multiple lots can be awarded to a single entity and documented in one contract award; a single lot can also be awarded to multiple entities, forming multiple contract awards; further a single contract award can include one or multiple lots. On TED, each tender and its corresponding contract award(s) has a structured XML file documenting key elements of information. We refer to these as ‘tender XML’ and ‘award XML’. An example of a tender XML is shown in Figure 1. Award XMLs generally follow the same structure. Tender XMLs document information such as the buyer, the lots, items of lots, contract criteria, etc. Award XMLs document the buyer, the lots, the awarded suppliers for each lot, contract value, quantity, etc. Each tender may also have a collection of ‘attachment documents’ that provide further details of the tender, especially on lots and items (‘tender attachments’) Given the availability of tender and award XMLs, one may consider the task of developing and populating the database to be easy. However, the data in reality is far more complicated. First and foremost, the tender and award XMLs are often incomplete. The predominant missing information is lot and item information. As an example, the tender XML for ‘2019/S 180-437985’, mentions 47 lots in the tender, without detailing the specific items but a lot reference number. This critical information is available from a bulk download of 7 tender attachments (PDFs). Both the tender and award XMLs then cross-reference these data sources through the use of the lot references. Recovering such information is crucial to building the supplier risk profile, which needs to account for the range and quantity of products that a supplier has supplied in the past. Second, not every tender attachment is relevant for our aim. Among those for ‘2019/S 180-437985’, two PDFs list the actual lots and items (e.g., Figure 2), while others document specifications, requirements, regulations and protocols etc. Third, not every page of a relevant attachment contains relevant information. For example, Figure 3 shows that in another tender, lots and items are described in one page but different sections of a long document. Fourth, as it is already shown in Figures 2 and 3, there is a significant discrepancy in how lot and item information is described within the same country, or indeed, even the same organisation. This discrepancy has been observed at different levels such as: the use of structured formatting (e.g., free text v.s. tables/lists); the amount of information encoded (e.g., the table in Figure 2 lists 16 columns (attributes) for each item) even for the same kinds of products/services; and the semantics of structure where structures are adopted (e.g., the order and names of columns). Such a high level of complexity and inconsistency could be one major reason why there has been a lack of text mining and NLP studies or applications for healthcare procurement. Authors:
(1) Ziqi Zhang*, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Ziqi.Zhang@sheffield.ac.uk);
(2) Tomas Jasaitis, Vamstar Ltd., London (Tomas.Jasaitis@vamstar.io);
(3) Richard Freeman, Vamstar Ltd., London (Richard.Freeman@vamstar.io);
(4) Rowida Alfrjani, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Rowida.Alfrjani@sheffield.ac.uk);
(5) Adam Funk, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Adam.Funk@sheffield.ac.uk). This paper is available on arxiv under CC BY 4.0 license. [1] https://ted.europa.eu/udl?uri=TED:NOTICE:437985-2019:TEXT:EN:HTML, last accessed: Nov 2022 Table of Links Abstract and Introduction Domain and Task
2.1. Data sources and complexity
2.2. Task definition Related Work
3.1. Text mining and NLP research overview
3.2. Text mining and NLP in industry use
3.3. Text mining and NLP for procurement
3.4. Conclusion from literature review Proposed Methodology
4.1. Domain knowledge
4.2. Content extraction
4.3. Lot zoning
4.4. Lot item detection
4.5. Lot parsing
4.6. XML parsing, data joining, and risk indices development Experiment and Demonstration
5.1. Component evaluation
5.2. System demonstration Discussion
6.1. The ‘industry’ focus of the project
6.2. Data heterogeneity, multilingual and multi-task nature
6.3. The dilemma of algorithmic choices
6.4. The cost of training data Conclusion, Acknowledgements, and References Abstract and Introduction Abstract and Introduction Abstract and Introduction Abstract and Introduction Domain and Task 2.1. Data sources and complexity 2.2. Task definition Domain and Task Domain and Task 2.1. Data sources and complexity 2.1. Data sources and complexity 2.2. Task definition 2.2. Task definition Related Work 3.1. Text mining and NLP research overview 3.2. Text mining and NLP in industry use 3.3. Text mining and NLP for procurement 3.4. Conclusion from literature review Related Work Related Work 3.1. Text mining and NLP research overview 3.1. Text mining and NLP research overview 3.2. Text mining and NLP in industry use 3.2. Text mining and NLP in industry use 3.3. Text mining and NLP for procurement 3.3. Text mining and NLP for procurement 3.4. Conclusion from literature review 3.4. Conclusion from literature review Proposed Methodology 4.1. Domain knowledge 4.2. Content extraction 4.3. Lot zoning 4.4. Lot item detection 4.5. Lot parsing 4.6. XML parsing, data joining, and risk indices development Proposed Methodology Proposed Methodology Proposed Methodology 4.1. Domain knowledge 4.1. Domain knowledge 4.2. Content extraction 4.2. Content extraction 4.3. Lot zoning 4.3. Lot zoning 4.4. Lot item detection 4.4. Lot item detection 4.5. Lot parsing 4.5. Lot parsing 4.6. XML parsing, data joining, and risk indices development 4.6. XML parsing, data joining, and risk indices development Experiment and Demonstration 5.1. Component evaluation 5.2. System demonstration Experiment and Demonstration Experiment and Demonstration 5.1. Component evaluation 5.1. Component evaluation 5.2. System demonstration 5.2. System demonstration Discussion 6.1. The ‘industry’ focus of the project 6.2. Data heterogeneity, multilingual and multi-task nature 6.3. The dilemma of algorithmic choices 6.4. The cost of training data Discussion Discussion 6.1. The ‘industry’ focus of the project 6.1. The ‘industry’ focus of the project 6.2. Data heterogeneity, multilingual and multi-task nature 6.2. Data heterogeneity, multilingual and multi-task nature 6.3. The dilemma of algorithmic choices 6.3. The dilemma of algorithmic choices 6.4. The cost of training data 6.4. The cost of training data Conclusion, Acknowledgements, and References Conclusion, Acknowledgements, and References Conclusion, Acknowledgements, and References Conclusion, Acknowledgements, and References 2. Domain and Task This work focuses on healthcare procurement, which has been rarely studied in the literature. The primary goal of the project is to develop a platform that allows the dynamic creation of a ‘supplier risk profile’ for each healthcare supplier. We envisage such a profile to consist of different ‘indices’ that evaluate different perspectives (e.g, capacity for supplying certain products, geographical coverage) of ‘risks’ for potential buyers to sign contracts with the supplier. This would enable questions such as ‘who are the suppliers able to supply this kind of medication’, ‘to what extent are they capable of supplying for this country’, or ‘are they able to supply such quantity’ to be easily answered. Such questions are often crucial for buyer decision making. However, the current procurement process relies on manually sifting through multiple lengthy documents to seek answers. This is a very resource consuming process. Understandably, an enabler of our primary goal would be a structured database of healthcare suppliers’ historical contract data. Thus the secondary goal of the project is to develop such a database and populate it with historical healthcare procurement data. While public procurement data is vastly available, as we shall explain in the following, there is a mixture of structured, semi-structured, and unstructured multilingual data that need to be mined and linked. Therefore, a major part of the project’s work is developing text mining and NLP solutions that automatically process large quantities of unstructured procurement data to mine information that can be used to populate the database. The goal of this article is therefore, to report the development of these text mining and NLP methods. 2.1. Data sources and complexity The project targets procurement data from the ‘Tenders Electronic Daily’ (TED) platform, which is used by the EU governments to publish their public procurement related projects. TED publishes over 460,000 calls for tenders and contract awards in 26 official European languages per year, for about 420 billion euro of value. Each tender may be divided into multiple ‘lots’, where a lot is the smallest contract unit. Each lot may contain multiple items that are required. As an example, tender notice ‘2019/S 180-437985’[1] lists 47 lots from an NHS (UK) tender, with their sizes ranging from 2 to over 30 items. If a tender secures successful bids, a ‘contract award’ (or multiple awards) will be made and recorded in TED for the tender. In the following, for the sake of explainability, we assume there is one award for each tender (however in practice, our methods are applied to all awards that are available for a tender). Note the lots offered in a tender and the contract awards form a ‘many-to-many’ relationship. Namely, multiple lots can be awarded to a single entity and documented in one contract award; a single lot can also be awarded to multiple entities, forming multiple contract awards; further a single contract award can include one or multiple lots. On TED, each tender and its corresponding contract award(s) has a structured XML file documenting key elements of information. We refer to these as ‘tender XML’ and ‘award XML’. An example of a tender XML is shown in Figure 1. Award XMLs generally follow the same structure. Tender XMLs document information such as the buyer, the lots, items of lots, contract criteria, etc. Award XMLs document the buyer, the lots, the awarded suppliers for each lot, contract value, quantity, etc. Each tender may also have a collection of ‘attachment documents’ that provide further details of the tender, especially on lots and items (‘tender attachments’) Given the availability of tender and award XMLs, one may consider the task of developing and populating the database to be easy. However, the data in reality is far more complicated. First and foremost, the tender and award XMLs are often incomplete. The predominant missing information is lot and item information. As an example, the tender XML for ‘2019/S 180-437985’, mentions 47 lots in the tender, without detailing the specific items but a lot reference number. This critical information is available from a bulk download of 7 tender attachments (PDFs). Both the tender and award XMLs then cross-reference these data sources through the use of the lot references. Recovering such information is crucial to building the supplier risk profile, which needs to account for the range and quantity of products that a supplier has supplied in the past. Second, not every tender attachment is relevant for our aim. Among those for ‘2019/S 180-437985’, two PDFs list the actual lots and items (e.g., Figure 2), while others document specifications, requirements, regulations and protocols etc. Third, not every page of a relevant attachment contains relevant information. For example, Figure 3 shows that in another tender, lots and items are described in one page but different sections of a long document. Fourth, as it is already shown in Figures 2 and 3, there is a significant discrepancy in how lot and item information is described within the same country, or indeed, even the same organisation. This discrepancy has been observed at different levels such as: the use of structured formatting (e.g., free text v.s. tables/lists); the amount of information encoded (e.g., the table in Figure 2 lists 16 columns (attributes) for each item) even for the same kinds of products/services; and the semantics of structure where structures are adopted (e.g., the order and names of columns). Such a high level of complexity and inconsistency could be one major reason why there has been a lack of text mining and NLP studies or applications for healthcare procurement. Authors: (1) Ziqi Zhang*, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Ziqi.Zhang@sheffield.ac.uk); (2) Tomas Jasaitis, Vamstar Ltd., London (Tomas.Jasaitis@vamstar.io); (3) Richard Freeman, Vamstar Ltd., London (Richard.Freeman@vamstar.io); (4) Rowida Alfrjani, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Rowida.Alfrjani@sheffield.ac.uk); (5) Adam Funk, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Adam.Funk@sheffield.ac.uk). Authors: Authors: (1) Ziqi Zhang*, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Ziqi.Zhang@sheffield.ac.uk); (2) Tomas Jasaitis, Vamstar Ltd., London (Tomas.Jasaitis@vamstar.io); (3) Richard Freeman, Vamstar Ltd., London (Richard.Freeman@vamstar.io); (4) Rowida Alfrjani, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Rowida.Alfrjani@sheffield.ac.uk); (5) Adam Funk, Information School, the University of Sheffield, Regent Court, Sheffield, UKS1 4DP (Adam.Funk@sheffield.ac.uk). This paper is available on arxiv under CC BY 4.0 license. This paper is available on arxiv under CC BY 4.0 license. available on arxiv available on arxiv [1] https://ted.europa.eu/udl?uri=TED:NOTICE:437985-2019:TEXT:EN:HTML, last accessed: Nov 2022

How Healthcare Procurement Data is Being Used to Evaluate Supplier Reliability

የጤና እንክብካቤ ግዥ መረጃ የአቅራቢውን አስተማማኝነት ለመገምገም እንዴት ጥቅም ላይ እንደሚውል

Com s'utilitzen les dades d'adquisició d'assistència sanitària per avaluar la fiabilitat dels proveïdors

Hvordan sundhedsindkøbsdata bliver brugt til at evaluere leverandørens pålidelighed

Cómo se utilizan los datos de adquisiciones sanitarias para evaluar la fiabilidad de los proveedores

Como se usan os datos de adquisición de asistencia sanitaria para avaliar a fiabilidade dos provedores

ヘルスケア調達データがどのようにサプライヤーの信頼性を評価するために使用されているか

របៀបដែលទិន្នន័យលទ្ធកម្មការថែទាំសុខភាពត្រូវបានប្រើប្រាស់ដើម្បីវាយតម្លៃភាពជឿជាក់របស់អ្នកផ្គត់ផ្គង់

ວິທີການຂໍ້ມູນການຈັດຊື້ການດູແລສຸຂະພາບຖືກໃຊ້ເພື່ອປະເມີນຄວາມຫນ້າເຊື່ອຖືຂອງຜູ້ສະຫນອງ

Kamoo Datha ya Theko ya Tlhokomelo ya Maphelo e Šomišwago ka gona go Lekola Botshepegi bja Moabi

Sağlık Hizmeti Tedarik Verileri Tedarikçi Güvenilirliğini Değerlendirmek İçin Nasıl Kullanılıyor?

Як дані закупівель у сфері охорони здоров’я використовуються для оцінки надійності постачальників

ہیلتھ کیئر پروکیورمنٹ ڈیٹا کو سپلائی کرنے والے کی وشوسنییتا کا اندازہ لگانے کے لیے کس طرح استعمال کیا جا رہا ہے۔

Using AI to Analyze Healthcare Procurement Documents and Assess Supplier Risks

The pressure on healthcare systems to process vast amounts of patient data efficiently has never been greater. The growing need for real-time insights in clinical trials, patient management, and diagnostics is driving the demand for advanced data solutions. According to a 2023 report by IDC, the global healthcare data analytics market is projected to reach $45 billion by 2027. However, as data volumes continue to grow, traditional systems are struggling to keep up, leading to delays in drug development and clinical trials. One of the most critical challenges today is how to handle large datasets without compromising speed or accuracy. For pharmaceutical companies, timely data analysis can mean the difference between a successful trial and costly delays. This is where innovative solutions in data processing become essential for accelerating drug development and improving patient outcomes. Recognizing these challenges, Kirill Sergeev, a seasoned backend developer and machine learning engineer, has been developing cutting-edge systems that streamline the processing of medical data. By leveraging high-performance technologies, Sergeev has optimized data pipelines to enable companies to handle up to 100 terabytes of data daily with remarkable efficiency. "The key to managing large datasets efficiently lies in creating systems that are not just fast but also flexible enough to handle complex, dynamic data flows. In the medical field, where data needs to be processed quickly and securely, we cannot afford inefficiencies,"
-Kirill Sergeev One of the significant challenges in clinical data management is the lengthy process of deploying new machine learning models. Previously, deploying algorithms for clinical trials could take anywhere from two to three days, slowing down the ability to respond to new data. By redesigning data pipelines and integrating robust CI/CD processes, Sergeev has successfully reduced this time to just 1-2 hours. This streamlined process allows pharmaceutical companies to test and integrate new findings more quickly, ultimately accelerating the drug development timeline. "In any system dealing with high volumes of data, efficiency is key. It’s not just about handling data faster; it’s about ensuring that the results are accurate, actionable, and available immediately when needed," Sergeev adds. Speed and accuracy are essential in sectors where real-time insights can significantly impact patient outcomes. Sergeev’s work in optimizing data systems has cut response times for processing large volumes of medical data from 1.5 minutes to just 500 milliseconds. This level of performance is crucial for enabling healthcare providers to make timely decisions based on up-to-date information. By mostly adapting two types of approaches:  batch based and lambda-based, Sergeev has developed a hybrid architecture that ensures secure, scalable, and efficient data processing. This approach enables rapid data retrieval and real-time analysis, which is vital for managing clinical trials and patient records. While the healthcare sector benefits significantly from these advancements, Sergeev’s methodologies are also transforming other industries, such as fintech and e-commerce. By applying similar techniques, companies in these sectors have achieved substantial gains in efficiency. In a fintech project, for instance, Sergeev’s microservice architecture reduced transaction processing times by 35%, while also enhancing system security. In the e-commerce domain, his methods led to a 40% boost in operational efficiency by optimizing real-time inventory management systems. "The approach is universal," Sergeev notes. "Whether it’s healthcare, finance, or retail, the key is to build systems that are scalable and resilient to handle the increasing demands of modern data workloads." The future of healthcare lies in leveraging real-time data to drive faster and more accurate decision-making. As the sector continues to embrace data-driven practices, innovations like those developed by Sergeev will be crucial for enhancing patient care and speeding up drug development. "I think the future of data processing in healthcare lies in real-time insights that can inform quicker decisions. We’re only scratching the surface, but the potential to revolutionize patient care and drug development is immense," Sergeev concludes. By addressing the pressing needs of modern healthcare data management, Kirill Sergeev’s work is paving the way for a more efficient, data-driven approach that not only benefits the medical industry but also sets new standards for data processing in other high-load sectors. The pressure on healthcare systems to process vast amounts of patient data efficiently has never been greater. The growing need for real-time insights in clinical trials, patient management, and diagnostics is driving the demand for advanced data solutions. According to a 2023 report by IDC, the global healthcare data analytics market is projected to reach $45 billion by 2027. However, as data volumes continue to grow, traditional systems are struggling to keep up, leading to delays in drug development and clinical trials. One of the most critical challenges today is how to handle large datasets without compromising speed or accuracy. For pharmaceutical companies, timely data analysis can mean the difference between a successful trial and costly delays. This is where innovative solutions in data processing become essential for accelerating drug development and improving patient outcomes. Recognizing these challenges, Kirill Sergeev, a seasoned backend developer and machine learning engineer, has been developing cutting-edge systems that streamline the processing of medical data. By leveraging high-performance technologies, Sergeev has optimized data pipelines to enable companies to handle up to 100 terabytes of data daily with remarkable efficiency. "The key to managing large datasets efficiently lies in creating systems that are not just fast but also flexible enough to handle complex, dynamic data flows. In the medical field, where data needs to be processed quickly and securely, we cannot afford inefficiencies," -Kirill Sergeev "The key to managing large datasets efficiently lies in creating systems that are not just fast but also flexible enough to handle complex, dynamic data flows. In the medical field, where data needs to be processed quickly and securely, we cannot afford inefficiencies," "The key to managing large datasets efficiently lies in creating systems that are not just fast but also flexible enough to handle complex, dynamic data flows. In the medical field, where data needs to be processed quickly and securely, we cannot afford inefficiencies," -Kirill Sergeev One of the significant challenges in clinical data management is the lengthy process of deploying new machine learning models. Previously, deploying algorithms for clinical trials could take anywhere from two to three days, slowing down the ability to respond to new data. By redesigning data pipelines and integrating robust CI/CD processes, Sergeev has successfully reduced this time to just 1-2 hours. This streamlined process allows pharmaceutical companies to test and integrate new findings more quickly, ultimately accelerating the drug development timeline. "In any system dealing with high volumes of data, efficiency is key. It’s not just about handling data faster; it’s about ensuring that the results are accurate, actionable, and available immediately when needed," Sergeev adds. Speed and accuracy are essential in sectors where real-time insights can significantly impact patient outcomes. Sergeev’s work in optimizing data systems has cut response times for processing large volumes of medical data from 1.5 minutes to just 500 milliseconds. This level of performance is crucial for enabling healthcare providers to make timely decisions based on up-to-date information. By mostly adapting two types of approaches:  batch based and lambda-based, Sergeev has developed a hybrid architecture that ensures secure, scalable, and efficient data processing. This approach enables rapid data retrieval and real-time analysis, which is vital for managing clinical trials and patient records. While the healthcare sector benefits significantly from these advancements, Sergeev’s methodologies are also transforming other industries, such as fintech and e-commerce. By applying similar techniques, companies in these sectors have achieved substantial gains in efficiency. In a fintech project, for instance, Sergeev’s microservice architecture reduced transaction processing times by 35%, while also enhancing system security. In the e-commerce domain, his methods led to a 40% boost in operational efficiency by optimizing real-time inventory management systems. "The approach is universal," Sergeev notes. "Whether it’s healthcare, finance, or retail, the key is to build systems that are scalable and resilient to handle the increasing demands of modern data workloads." The future of healthcare lies in leveraging real-time data to drive faster and more accurate decision-making. As the sector continues to embrace data-driven practices, innovations like those developed by Sergeev will be crucial for enhancing patient care and speeding up drug development. "I think the future of data processing in healthcare lies in real-time insights that can inform quicker decisions. We’re only scratching the surface, but the potential to revolutionize patient care and drug development is immense," Sergeev concludes. By addressing the pressing needs of modern healthcare data management, Kirill Sergeev’s work is paving the way for a more efficient, data-driven approach that not only benefits the medical industry but also sets new standards for data processing in other high-load sectors.

Developer Kirill Sergeev Speaks on Empowering Healthcare System with Latest AI-solutions 

ገንቢ ኪሪል ሰርጌቭ የጤና እንክብካቤ ስርዓትን ስለማብቃት ከቅርብ ጊዜ AI-መፍትሄዎች ጋር ይናገራል 

Udvikler Kirill Sergeev taler om at styrke sundhedssystemet med de nyeste AI-løsninger 

El desarrollador Kirill Sergeev habla sobre cómo potenciar el sistema sanitario con las últimas soluciones de inteligencia artificial

Programer Kirill Sergeev govori o osnaživanju zdravstvenog sustava s najnovijim AI-rješenjima 

Kirill Szergejev fejlesztő beszél az egészségügyi rendszer megerősítéséről a legújabb mesterségesintelligencia-megoldásokkal 

開発者のキリル・セルゲイフが最新の AI ソリューションによるヘルスケア システムの強化について語る

Әзірлеуші Кирилл Сергеев денсаулық сақтау жүйесін соңғы AI шешімдерімен кеңейту туралы сөйлейді 

Mobongisi Kirill Sergeev Alobeli kopesa nguya na Système ya soins de santé na ba AI-solutions ya sika 

Mohlami Kirill Sergeev O Bua ka Matlafatsa Tshepedišo ya Tlhokomelo ya Maphelo ka Ditharollo tša Morago-rago tša AI 

Dezvoltatorul Kirill Sergeev vorbește despre abilitarea sistemului de sănătate cu cele mai recente soluții AI 

Програмер Кирилл Сергеев говори о оснаживању здравственог система са најновијим АИ-решењима 

Geliştirici Kirill Sergeev, Sağlık Sistemini En Son Yapay Zeka Çözümleriyle Güçlendirme Konusunda Konuşuyor

Developing a Patient-Friendly EHR Platform: A Healthcare Case Study by Maruti Techlabs

Desarrollo de una plataforma de EHR amigable para el paciente: un estudio de caso de atención médica de Maruti Techlabs

患者に優しい EHR プラットフォームの開発: Maruti Techlabs によるヘルスケアのケース スタディ

პაციენტისთვის მეგობრული EHR პლატფორმის შემუშავება: ჯანდაცვის საქმის შესწავლა Maruti Techlabs-ის მიერ

Opracowanie przyjaznej pacjentowi platformy EHR: studium przypadku w opiece zdrowotnej autorstwa Maruti Techlabs

Huk Plataforma EHR Paciente-Amigo ruway: Huk Estudio de caso de Salud kaqmanta Maruti Techlabs kaqmanta

රෝගීන්ට හිතකර EHR වේදිකාවක් සංවර්ධනය කිරීම: Maruti Techlabs විසින් සෞඛ්‍ය සේවා සිද්ධි අධ්‍යයනයක්

Kugadzira Murwere-Ane Hushamwari EHR Platform: A Healthcare Nyaya Yekudzidza naMaruti Techlabs

நோயாளிக்கு உகந்த EHR பிளாட்ஃபார்மை உருவாக்குதல்: மாருதி டெக்லேப்ஸ் மூலம் ஒரு ஹெல்த்கேர் கேஸ் ஸ்டடி

ምምዕባል ንሕሙም ዝምችእ EHR ፕላትፎርም: መጽናዕቲ ክንክን ጥዕና ብማሩቲ ቴክላብስ

Näsaglara dostlukly EHR platformasyny ösdürmek: Maruti Techlabs tarapyndan saglygy goraýyş meselesi

Ku tumbuluxa Pulatifomo ya EHR leyi nga na Xinghana na Muvabyi: Dyondzo ya Xiyimo xa Nkhathalelo wa Rihanyo hi Maruti Techlabs

ایک مریض کے لئے دوستانہ EHR پلیٹ فارم تیار کرنا: ماروتی ٹیک لیبز کے ذریعہ ایک ہیلتھ کیئر کیس اسٹڈی

The Startups of The Year 2024 showcases exceptional companies across 100 industries. Nominations are based on regional and industrial excellence, not just location. This series will detail our key industries and demonstrate how HackerNoon can help you explore them further. Innovation is the key to improving healthcare, and the goal must be to make it affordable and accessible to everyone — Bill Gates Healthcare is a core area of interest for any nation around the globe, and with the advent of new technologies, such as artificial intelligence, the world can expect to see new forms of preventive care, diagnosis, treatment, and rehabilitation. Using tech to solve some of the pressing healthcare issues around the globe, such as by tracking and containing possible outbreaks, verifying that medicines are reaching those in need, and safeguarding access to patients' data, startups are playing a critical role in ensuring the industry continues to tackle challenges in new and innovative ways. Startups of The Year 2024 & Healthcare HackerNoon's Startups of The Year is celebrating the healthcare industry by shedding light on tech's rising stars across several industries, including: Healthcare Tech
Neuroscience
Fitness
Health and Wellness
Health Data Analytics A WORD FROM OUR SPONSORS:
“Startups are the heartbeat of Notion. We build for them and with them, constantly iterating on tools that empower them to focus on innovation and creativity. We are proud of this partnership with HackerNoon and excited to support the next generation of groundbreaking companies.”- Anastasia Crew, Head of Notion Startups Nominate and vote for your favorite Healthcare companies here! If you're a nominee, share more by completing the Healthcare Startup Interview Template. Healthcare on HackerNoon HackerNoon covers multiple categories from this industry, such as Healthcare, Healthcare Tech, Fitness, Wellness, and more. To help you get started on your journey through this dynamic industry, here are some stories you might find interesting: Start Writing About Healthcare Today! Click here or use this writing template! Healthcare Stories to Kickstart Your Journey The Quiet Crisis That Is Stealing Our Health (and How to Get It Back) - Insights From Dr. Eric Berg by Scott D. Clary I recently had the pleasure of interviewing Dr. Berg on my podcast, and let me tell you, he doesn't disappoint. Forget the fancy jargon and confusing studies. Dr. Berg breaks down complex health topics into simple, easy-to-understand terms that you can actually apply to your life. Whether you're struggling with weight loss, chronic health issues, or simply want to optimize your well-being, Dr. Berg's no-nonsense approach will empower you to take charge of your health and achieve your goals. https://hackernoon.com/the-quiet-crisis-that-is-stealing-our-health-and-how-to-get-it-back-insights-from-dr-eric-berg?embedable=true The Evolution of AI in Healthcare: From Ambitious Beginnings to What's Next by Mat Coolidge The journey of AI in healthcare can be categorized into three distinct waves. The first wave emerged in the aftermath of World War II. The second wave, spanning the 1980s, was marked by the development of expert systems. The third and current wave of AI began in the 2010s, characterized by the introduction of deep learning and neural networks. https://hackernoon.com/the-evolution-of-ai-in-healthcare-from-ambitious-beginnings-to-whats-next?embedable=true The Ethics of Automation in Medical Billing by Devin Partida Automation could do more harm than good if healthcare institutions don’t carefully consider integration-related ethical concerns. Fortunately, there are ways to ethically leverage the benefits of automation in health care. The healthcare industry leverages automation because it’s cost-effective and it improves productivity. https://hackernoon.com/the-ethics-of-automation-in-medical-billing?embedable=true Mental Health (Just Like The World) Is On Fire: Here's How It Can Be Put Out by Daria Leshchenko Maintaining a work-life balance is one of the most important things to support one’s mental well-being. Here are the steps that I take to remain focused and keep my mental health… well, healthy. I am a firm believer that there should be a clear goal for every action. Regular exercise is also a good way to improve the mood. https://hackernoon.com/mental-health-just-like-the-world-is-on-fire-heres-how-it-can-be-put-out?embedable=true Sweat Hero: Pioneering the Move-2-Earn Gaming Space with Fitness and NFTs by Ishan Pandey Sweat Hero is the first-ever Move-2-Earn game developed by the Sweat Economy. The game rewards users' physical movement with in-game currency. Sweat Hero's innovative approach incorporates dynamic NFTs that evolve based on the player's in-game progression and interaction. https://hackernoon.com/sweat-hero-pioneering-the-move-2-earn-gaming-space-with-fitness-and-nfts?embedable=true That’s all for today! PS: Remember to nominate and vote for your favorite Healthcare companies - do it here! About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. Visit our FAQ page to learn more. Download our design assets here. Check out the Startups of the Year Merch Shop here. HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool. Get your offer now! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. The Startups of The Year 2024 showcases exceptional companies across 100 industries. Nominations are based on regional and industrial excellence, not just location. This series will detail our key industries and demonstrate how HackerNoon can help you explore them further. The Startups of The Year 2024 showcases exceptional companies across 100 industries . Nominations are based on regional and industrial excellence, not just location. This series will detail our key industries and demonstrate how HackerNoon can help you explore them further. The Startups of The Year 2024 100 industries Innovation is the key to improving healthcare, and the goal must be to make it affordable and accessible to everyone — Bill Gates Innovation is the key to improving healthcare, and the goal must be to make it affordable and accessible to everyone — Bill Gates Healthcare is a core area of interest for any nation around the globe, and with the advent of new technologies, such as artificial intelligence, the world can expect to see new forms of preventive care, diagnosis, treatment, and rehabilitation. Healthcare Using tech to solve some of the pressing healthcare issues around the globe, such as by tracking and containing possible outbreaks, verifying that medicines are reaching those in need, and safeguarding access to patients' data, startups are playing a critical role in ensuring the industry continues to tackle challenges in new and innovative ways. Startups of The Year 2024 & Healthcare HackerNoon's Startups of The Year is celebrating the healthcare industry by shedding light on tech's rising stars across several industries, including: healthcare industry Healthcare Tech Neuroscience Fitness Health and Wellness Health Data Analytics Healthcare Tech Healthcare Tech Neuroscience Neuroscience Fitness Fitness Health and Wellness Health and Wellness Health Data Analytics Health Data Analytics A WORD FROM OUR SPONSORS: “Startups are the heartbeat of Notion. We build for them and with them, constantly iterating on tools that empower them to focus on innovation and creativity. We are proud of this partnership with HackerNoon and excited to support the next generation of groundbreaking companies.” - Anastasia Crew, Head of Notion Startups A WORD FROM OUR SPONSORS: “Startups are the heartbeat of Notion. We build for them and with them, constantly iterating on tools that empower them to focus on innovation and creativity. We are proud of this partnership with HackerNoon and excited to support the next generation of groundbreaking companies.” “Startups are the heartbeat of Notion . We build for them and with them, constantly iterating on tools that empower them to focus on innovation and creativity. We are proud of this partnership with HackerNoon and excited to support the next generation of groundbreaking companies.” Notion - Anastasia Crew, Head of Notion Startups Nominate and vote for your favorite Healthcare companies here! If you're a nominee, share more by completing the Healthcare Startup Interview Template. Nominate and vote for your favorite Healthcare companies here ! If you're a nominee, share more by completing the Healthcare Startup Interview Template . here Healthcare Startup Interview Template Healthcare on HackerNoon HackerNoon covers multiple categories from this industry, such as Healthcare , Healthcare Tech , Fitness , Wellness , and more. To help you get started on your journey through this dynamic industry, here are some stories you might find interesting: Healthcare Healthcare Tech Fitness Wellness Start Writing About Healthcare Today! Click here or use this writing template! Start Writing About Healthcare Today! Click here or use this writing template ! here here this writing template this writing template Healthcare Stories to Kickstart Your Journey Healthcare Stories to Kickstart Your Journey The Quiet Crisis That Is Stealing Our Health (and How to Get It Back) - Insights From Dr. Eric Berg by Scott D. Clary The Quiet Crisis That Is Stealing Our Health (and How to Get It Back) - Insights From Dr. Eric Berg by Scott D. Clary The Quiet Crisis That Is Stealing Our Health (and How to Get It Back) - Insights From Dr. Eric Ber g by Scott D. Clary The Quiet Crisis That Is Stealing Our Health (and How to Get It Back) - Insights From Dr. Eric Ber Scott D. Clary I recently had the pleasure of interviewing Dr. Berg on my podcast, and let me tell you, he doesn't disappoint. Forget the fancy jargon and confusing studies. Dr. Berg breaks down complex health topics into simple, easy-to-understand terms that you can actually apply to your life. Whether you're struggling with weight loss, chronic health issues, or simply want to optimize your well-being, Dr. Berg's no-nonsense approach will empower you to take charge of your health and achieve your goals. https://hackernoon.com/the-quiet-crisis-that-is-stealing-our-health-and-how-to-get-it-back-insights-from-dr-eric-berg?embedable=true https://hackernoon.com/the-quiet-crisis-that-is-stealing-our-health-and-how-to-get-it-back-insights-from-dr-eric-berg?embedable=true The Evolution of AI in Healthcare: From Ambitious Beginnings to What's Next by Mat Coolidge The Evolution of AI in Healthcare: From Ambitious Beginnings to What's Next by Mat Coolidge The Evolution of AI in Healthcare: From Ambitious Beginnings to What's Next by Mat Coolidge The Evolution of AI in Healthcare: From Ambitious Beginnings to What's Next Mat Coolidge The journey of AI in healthcare can be categorized into three distinct waves. The first wave emerged in the aftermath of World War II. The second wave, spanning the 1980s, was marked by the development of expert systems. The third and current wave of AI began in the 2010s, characterized by the introduction of deep learning and neural networks. https://hackernoon.com/the-evolution-of-ai-in-healthcare-from-ambitious-beginnings-to-whats-next?embedable=true https://hackernoon.com/the-evolution-of-ai-in-healthcare-from-ambitious-beginnings-to-whats-next?embedable=true The Ethics of Automation in Medical Billing by Devin Partida The Ethics of Automation in Medical Billing by Devin Partida The Ethics of Automation in Medical Billing by Devin Partida The Ethics of Automation in Medical Billing Devin Partida Automation could do more harm than good if healthcare institutions don’t carefully consider integration-related ethical concerns. Fortunately, there are ways to ethically leverage the benefits of automation in health care. The healthcare industry leverages automation because it’s cost-effective and it improves productivity. https://hackernoon.com/the-ethics-of-automation-in-medical-billing?embedable=true https://hackernoon.com/the-ethics-of-automation-in-medical-billing?embedable=true Mental Health (Just Like The World) Is On Fire: Here's How It Can Be Put Out by Daria Leshchenko Mental Health (Just Like The World) Is On Fire: Here's How It Can Be Put Out by Daria Leshchenko Mental Health (Just Like The World) Is On Fire: Here's How It Can Be Put Out by Daria Leshchenko Mental Health (Just Like The World) Is On Fire: Here's How It Can Be Put Out Daria Leshchenko Maintaining a work-life balance is one of the most important things to support one’s mental well-being. Here are the steps that I take to remain focused and keep my mental health… well, healthy. I am a firm believer that there should be a clear goal for every action. Regular exercise is also a good way to improve the mood. https://hackernoon.com/mental-health-just-like-the-world-is-on-fire-heres-how-it-can-be-put-out?embedable=true https://hackernoon.com/mental-health-just-like-the-world-is-on-fire-heres-how-it-can-be-put-out?embedable=true Sweat Hero: Pioneering the Move-2-Earn Gaming Space with Fitness and NFTs by Ishan Pandey Sweat Hero: Pioneering the Move-2-Earn Gaming Space with Fitness and NFTs by Ishan Pandey Sweat Hero: Pioneering the Move-2-Earn Gaming Space with Fitness and NFTs by Ishan Pandey Sweat Hero: Pioneering the Move-2-Earn Gaming Space with Fitness and NFTs Ishan Pandey Sweat Hero is the first-ever Move-2-Earn game developed by the Sweat Economy. The game rewards users' physical movement with in-game currency. Sweat Hero's innovative approach incorporates dynamic NFTs that evolve based on the player's in-game progression and interaction. https://hackernoon.com/sweat-hero-pioneering-the-move-2-earn-gaming-space-with-fitness-and-nfts?embedable=true https://hackernoon.com/sweat-hero-pioneering-the-move-2-earn-gaming-space-with-fitness-and-nfts?embedable=true That’s all for today! PS: Remember to nominate and vote for your favorite Healthcare companies - do it here! PS: Remember to nominate and vote for your favorite Healthcare companies - do it here ! here here About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. Startups of The Year 2024 many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview Evergreen Tech Company News Visit our FAQ page to learn more. FAQ page Download our design assets here . here Check out the Startups of the Year Merch Shop here . here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. startup-friendly packages Meet our sponsors: Wellfound: Join the #1 global, startup-focused community . At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months , to build and scale your company with one powerful tool. Get your offer now ! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Hubspot: Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection , businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection

Startups of The Year: Meet the Healthcare Industry

شركات ناشئة لهذا العام: تعرف على صناعة الرعاية الصحية

বছরের স্টার্টআপ: স্বাস্থ্যসেবা শিল্পের সাথে দেখা করুন

Startapi godine: Upoznajte industriju zdravstvene zaštite

Startups del año: conozca la industria de la salud

Startups pou ane a: Rankontre endistri swen sante a

Տարվա ստարտափներ. ծանոթացեք առողջապահության ոլորտին

今年のスタートアップ: ヘルスケア業界を知る

වසරේ ආරම්භක: සෞඛ්‍ය සේවා කර්මාන්තය හමුවන්න

Kutanga kweGore: Sangana neIndasitiri yehutano

Fillesat e Vitit: Njihuni me Industrinë e Kujdesit Shëndetësor

ናይዚ ዓመት ጀመርቲ ትካላት፡ ምስ ኢንዱስትሪ ክንክን ጥዕና ተራኸቡ።

Các công ty khởi nghiệp của năm: Gặp gỡ ngành chăm sóc sức khỏe

Is Artificial Intelligence in Healthcare a Ticking Time Bomb or Timely Solution?

Synthetic Data And Its Potential In Healthcare

البيانات الاصطناعية وإمكاناتها في مجال الرعاية الصحية

Сінтэтычныя дадзеныя і іх патэнцыял у ахове здароўя

সিন্থেটিক ডেটা এবং স্বাস্থ্যসেবায় এর সম্ভাব্যতা

Dades sintètiques i el seu potencial en l'assistència sanitària

Los datos sintéticos y su potencial en la atención sanitaria

合成データと医療におけるその可能性

Синтетикалык маалыматтар жана анын саламаттыкты сактоодогу потенциалы

Sintētiskie dati un to potenciāls veselības aprūpē

Синтетик өгөгдөл ба түүний эрүүл мэнд дэх боломж

Datha ya Maitirelo Le Bokgoni bja Yona Tlhokomelong ya Maphelo

Маълумоти синтетикӣ ва потенсиали он дар соҳаи тандурустӣ

Idatha yokwenziwa kunye nokubanakho kwayo kukhathalelo lwempilo

Jinesh Kumar Chinnathambi, a Solution Architect at a leading health insurance company, is using his real-world experience in the fields of Machine Learning (ML) and Artificial Intelligence (AI) to make the healthcare sector more patient-centric and improve patient care. People pursuing a career in healthcare IT are often driven by the aspiration to have a significant impact on people's lives. For Jinesh, the best way to do this in 2024 is by utilizing the problem-solving capabilities of technology to improve and streamline the healthcare industry. As he says, "The ever-changing healthcare landscape, with advancements such as Electronic Health Records (EHR), telemedicine, artificial intelligence, and predictive analytics transforming patient care, presents captivating challenges and opportunities for innovation. It provides the satisfaction of knowing that work in this field directly contributes to enhancing the quality, accessibility, and effectiveness of patient care, ultimately making healthcare more patient-centric." Combining the innovations and technologies in this healthcare IT, such as AI-driven diagnostics, predictive analytics, and personalized treatment plans, with the soft skills required in Healthcare roles, including problem-solving, analytical thinking, communication, and understanding of healthcare operations, has proven incredibly beneficial to both patients and healthcare professionals. Introducing Jinesh Kumar Chinnathambi Jinesh Kumar Chinnathambi's education began with a Bachelor's degree in computer science engineering, which gave him a strong foundation for his work in healthcare IT. During his studies, Jinesh focused on subjects at the intersection of technology and healthcare, including databases, data analysis, and healthcare systems. After graduating, he gained practical IT experience through entry-level roles and tech positions in the healthcare industry. He achieved further specialization in healthcare IT through certifications offered by AHIP (America's Health Insurance Plan) and has kept updated on new healthcare regulations, emerging technologies, and industry best practices to stay ahead of the curve. Networking with professionals, attending industry conferences, and keeping abreast of healthcare IT journals have provided valuable insights and helped him garner success in his career. As he says himself, "The journey into Healthcare IT involves a combination of education, practical experience, ongoing learning, and a dedication to enhancing healthcare delivery through technology." Jinesh has published numerous publications and pieces of academic research, including the well-received "Effective Cancer Recurrence Prediction using Healthcare Data Analytics with Machine Learning and Artificial Intelligence," "Leveraging Data Analytics with Artificial Intelligence to Detect and Close Health Care Gaps," “Harnessing Data Analytics and Artificial Intelligence in Healthcare,” and “Amplifying Big Data Utilization in Healthcare Analytics Through Cloud and Snowflake Migration.” His wide range of professional certifications and important achievements demonstrate his expertise in a highly competitive field. He is the only one of Elevance Health’s approximately 100,000 employees to hold four AWS certifications, including AWS Certified DevOps Professional, AWS Certified Solutions Architect Associate, AWS Certified Developer Associate, and AWS Certified SysOps Administrator Associate. He also holds a Sun Certified Java Professional (SCJP) certification and multiple America's Health Insurance Plans (AHIP) certifications, including Fundamentals of Healthcare Parts A and B and Basics of Managed Care Part A. In addition to all of this, Jinesh has been recognized with a 2024 Global Recognition Award for his notable healthcare and IT industry achievements. In August 2024, he also won the Cloud Innovator of the Year Award at the Business Innovation Awards 2024 in the Health Care/Information Technology category. This award recognizes outstanding achievements in cloud innovation. In addition to being awarded for his work, Jinesh was also named a judge for the Globee® Awards for Leadership in 2024, signifying a formal recognition of his commitment and significant contributions to his field, and received recognition for his role as judge at the Virginia Tech College Hackathon event. The Role of AI, ML, Data Analytics, Data Warehouses & Cloud Migration in Healthcare IT One of the major benefits of implementing technological advancements like AI and ML into healthcare IT is how they can be utilized to analyze vast amounts of healthcare data, accurately predict patient outcomes and improve treatment plans. A pivotal moment in Jinesh's IT career came with the advent of cloud computing, which reshaped the entire technology landscape. It was here, at the precipice of such a monumental technological change, that Jinesh realized just how beneficial such systems could be to the work he was doing. "Before the rise of cloud computing, businesses were required to establish, manage, and uphold their own expensive IT infrastructures,” recalls Jinesh. “Companies like Amazon, Google, and Microsoft began providing platforms that allowed access to databases, servers, software, and analytics via the internet. This led to a substantial reduction in the cost and complexity of IT operations, hastened innovation, and offered the flexibility to scale resources as needed. It empowered businesses to concentrate more on their core operations while leveraging state-of-the-art technology. Furthermore, cloud computing paved the way for a multitude of other technological advancements seen today, such as big data analytics and AI, which I am currently working on. It stands as a milestone that has redefined the possibilities of IT and continues to shape the future of technology." All of this works in tandem with the dedication of people in the healthcare field to craft a more patient-centric approach, providing personalized and timely care with revolutionary speed and precision. Real-World Studies and Applications By implementing these technological advancements into his established healthcare IT system, Jinesh has been able to successfully develop predictive analytics products to enhance patient care. His work has even been able to identify the signs and likelihood of cancer recurrence far earlier than previously thought possible, all thanks to data analytics, AI, and ML. By configuring AI models to run seamlessly on the cloud, Jinesh has contributed to accelerating predictive diagnoses, enhancing treatment plans, automating administrative tasks, and improving patient care. The strategic designs and technical expertise of solution architects are a vital part of shaping the future of AI-enabled, cloud-based healthcare systems. The impact of these projects has improved patient outcomes, reduced costs, improved efficiency, and helped to deliver more personalized care than ever before. Jinesh has worked tirelessly to guide and develop technology and tool solutions that improve data lineage adoption and governance by collaborating with technology partners to create a cloud-based data operation strategy. He oversaw a comprehensive cloud migration and data governance framework at Elevance Health, ensuring alignment with business objectives and HIPAA regulatory requirements, and also established a data council of senior executives across the enterprise to facilitate efficient collaboration on data initiatives. Furthermore, during his time at Elevance, he worked closely with the enterprise infrastructure and technology team to explore a cloud-based lake-house solution. Jinesh led the implementation of a data migration framework, including issue research, resolution processes, root cause analysis, reporting, data classifications and standards, and data quality validation and controls. He also developed a data governance framework to align with business objectives and HIPAA regulatory requirements, which supported the implementation of monolithic microservices for various use cases. He researched and recommended the appropriate Snowflake warehouse sizes after conducting several proofs of concept, resulting in optimal performance for middleware queries and reducing annual costs by 30%. One study estimated the national cost-savings in the United States from early diagnosis to be $26 billion per year. The Future of Healthcare Technology Jinesh's vision for the future of healthcare technology is one full of promise, continued improvement, and the potential to create a more patient-centric healthcare system that benefits everyone. He plans to work at the convergence of healthcare and technology to improve patient care by introducing new and advanced solutions and developing and managing Electronic Health Records (EHRs), health information exchanges, telemedicine services, and other initiatives to enhance healthcare coordination and accessibility, ultimately benefiting local communities. This will contribute to early disease detection, effective monitoring, decreased medical errors, and better communication between healthcare providers and patients. Jinesh Kumar Chinnathambi , a Solution Architect at a leading health insurance company, is using his real-world experience in the fields of Machine Learning (ML) and Artificial Intelligence (AI) to make the healthcare sector more patient-centric and improve patient care. Jinesh Kumar Chinnathambi Jinesh Kumar Chinnathambi People pursuing a career in healthcare IT are often driven by the aspiration to have a significant impact on people's lives. For Jinesh, the best way to do this in 2024 is by utilizing the problem-solving capabilities of technology to improve and streamline the healthcare industry. As he says, "The ever-changing healthcare landscape, with advancements such as Electronic Health Records (EHR), telemedicine, artificial intelligence, and predictive analytics transforming patient care, presents captivating challenges and opportunities for innovation. It provides the satisfaction of knowing that work in this field directly contributes to enhancing the quality, accessibility, and effectiveness of patient care, ultimately making healthcare more patient-centric." Combining the innovations and technologies in this healthcare IT, such as AI-driven diagnostics, predictive analytics, and personalized treatment plans, with the soft skills required in Healthcare roles, including problem-solving, analytical thinking, communication, and understanding of healthcare operations, has proven incredibly beneficial to both patients and healthcare professionals. Introducing Jinesh Kumar Chinnathambi Jinesh Kumar Chinnathambi's education began with a Bachelor's degree in computer science engineering, which gave him a strong foundation for his work in healthcare IT. During his studies, Jinesh focused on subjects at the intersection of technology and healthcare, including databases, data analysis, and healthcare systems. After graduating, he gained practical IT experience through entry-level roles and tech positions in the healthcare industry. He achieved further specialization in healthcare IT through certifications offered by AHIP (America's Health Insurance Plan) and has kept updated on new healthcare regulations, emerging technologies, and industry best practices to stay ahead of the curve. Networking with professionals, attending industry conferences, and keeping abreast of healthcare IT journals have provided valuable insights and helped him garner success in his career. As he says himself, "The journey into Healthcare IT involves a combination of education, practical experience, ongoing learning, and a dedication to enhancing healthcare delivery through technology." Jinesh has published numerous publications and pieces of academic research, including the well-received " Effective Cancer Recurrence Prediction using Healthcare Data Analytics with Machine Learning and Artificial Intelligence ," " Leveraging Data Analytics with Artificial Intelligence to Detect and Close Health Care Gaps ," “ Harnessing Data Analytics and Artificial Intelligence in Healthcare ,” and “ Amplifying Big Data Utilization in Healthcare Analytics Through Cloud and Snowflake Migration .” Effective Cancer Recurrence Prediction using Healthcare Data Analytics with Machine Learning and Artificial Intelligence Effective Cancer Recurrence Prediction using Healthcare Data Analytics with Machine Learning and Artificial Intelligence Leveraging Data Analytics with Artificial Intelligence to Detect and Close Health Care Gaps Leveraging Data Analytics with Artificial Intelligence to Detect and Close Health Care Gaps Harnessing Data Analytics and Artificial Intelligence in Healthcare Harnessing Data Analytics and Artificial Intelligence in Healthcare Amplifying Big Data Utilization in Healthcare Analytics Through Cloud and Snowflake Migration Amplifying Big Data Utilization in Healthcare Analytics Through Cloud and Snowflake Migration His wide range of professional certifications and important achievements demonstrate his expertise in a highly competitive field. He is the only one of Elevance Health’s approximately 100,000 employees to hold four AWS certifications, including AWS Certified DevOps Professional, AWS Certified Solutions Architect Associate, AWS Certified Developer Associate, and AWS Certified SysOps Administrator Associate. He also holds a Sun Certified Java Professional (SCJP) certification and multiple America's Health Insurance Plans (AHIP) certifications, including Fundamentals of Healthcare Parts A and B and Basics of Managed Care Part A. In addition to all of this, Jinesh has been recognized with a 2024 Global Recognition Award for his notable healthcare and IT industry achievements. Global Recognition Award Global Recognition Award In August 2024, he also won the Cloud Innovator of the Year Award at the Business Innovation Awards 2024 in the Health Care/Information Technology category. This award recognizes outstanding achievements in cloud innovation. In addition to being awarded for his work, Jinesh was also named a judge for the Globee® Awards for Leadership in 2024, signifying a formal recognition of his commitment and significant contributions to his field, and received recognition for his role as judge at the Virginia Tech College Hackathon event . Globee® Awards for Leadership Globee® Awards for Leadership Virginia Tech College Hackathon event Virginia Tech College Hackathon event The Role of AI, ML, Data Analytics, Data Warehouses & Cloud Migration in Healthcare IT One of the major benefits of implementing technological advancements like AI and ML into healthcare IT is how they can be utilized to analyze vast amounts of healthcare data, accurately predict patient outcomes and improve treatment plans. A pivotal moment in Jinesh's IT career came with the advent of cloud computing, which reshaped the entire technology landscape. It was here, at the precipice of such a monumental technological change, that Jinesh realized just how beneficial such systems could be to the work he was doing. "Before the rise of cloud computing, businesses were required to establish, manage, and uphold their own expensive IT infrastructures,” recalls Jinesh. “Companies like Amazon, Google, and Microsoft began providing platforms that allowed access to databases, servers, software, and analytics via the internet. This led to a substantial reduction in the cost and complexity of IT operations, hastened innovation, and offered the flexibility to scale resources as needed. It empowered businesses to concentrate more on their core operations while leveraging state-of-the-art technology. Furthermore, cloud computing paved the way for a multitude of other technological advancements seen today, such as big data analytics and AI, which I am currently working on. It stands as a milestone that has redefined the possibilities of IT and continues to shape the future of technology." All of this works in tandem with the dedication of people in the healthcare field to craft a more patient-centric approach, providing personalized and timely care with revolutionary speed and precision. Real-World Studies and Applications By implementing these technological advancements into his established healthcare IT system, Jinesh has been able to successfully develop predictive analytics products to enhance patient care. His work has even been able to identify the signs and likelihood of cancer recurrence far earlier than previously thought possible, all thanks to data analytics, AI, and ML. By configuring AI models to run seamlessly on the cloud, Jinesh has contributed to accelerating predictive diagnoses, enhancing treatment plans, automating administrative tasks, and improving patient care. The strategic designs and technical expertise of solution architects are a vital part of shaping the future of AI-enabled, cloud-based healthcare systems. The impact of these projects has improved patient outcomes, reduced costs, improved efficiency, and helped to deliver more personalized care than ever before. Jinesh has worked tirelessly to guide and develop technology and tool solutions that improve data lineage adoption and governance by collaborating with technology partners to create a cloud-based data operation strategy. He oversaw a comprehensive cloud migration and data governance framework at Elevance Health, ensuring alignment with business objectives and HIPAA regulatory requirements, and also established a data council of senior executives across the enterprise to facilitate efficient collaboration on data initiatives. Furthermore, during his time at Elevance, he worked closely with the enterprise infrastructure and technology team to explore a cloud-based lake-house solution. Jinesh led the implementation of a data migration framework, including issue research, resolution processes, root cause analysis, reporting, data classifications and standards, and data quality validation and controls. He also developed a data governance framework to align with business objectives and HIPAA regulatory requirements, which supported the implementation of monolithic microservices for various use cases. He researched and recommended the appropriate Snowflake warehouse sizes after conducting several proofs of concept, resulting in optimal performance for middleware queries and reducing annual costs by 30%. One study estimated the national cost-savings in the United States from early diagnosis to be $26 billion per year. One study estimated the national cost-savings One study estimated the national cost-savings The Future of Healthcare Technology Jinesh's vision for the future of healthcare technology is one full of promise, continued improvement, and the potential to create a more patient-centric healthcare system that benefits everyone. He plans to work at the convergence of healthcare and technology to improve patient care by introducing new and advanced solutions and developing and managing Electronic Health Records (EHRs), health information exchanges, telemedicine services, and other initiatives to enhance healthcare coordination and accessibility, ultimately benefiting local communities. This will contribute to early disease detection, effective monitoring, decreased medical errors, and better communication between healthcare providers and patients.

How AI and Machine Learning Are Making the Healthcare Sector More Patient-centric

እንዴት AI እና ማሽን መማር የጤና አጠባበቅ ሴክተሩን የበለጠ ታጋሽ ተኮር እያደረጉት ነው።

Süni intellekt və Maşın Öyrənməsi Səhiyyə Sektorunu necə daha xəstə mərkəzli edir

Com la IA i l'aprenentatge automàtic estan fent que el sector sanitari sigui més centrat en el pacient

Jak umělá inteligence a strojové učení dělají sektor zdravotnictví více zaměřený na pacienta

Cómo la IA y el aprendizaje automático están haciendo que el sector sanitario esté más centrado en el paciente

Comment l'IA et l'apprentissage automatique rendent le secteur de la santé plus centré sur le patient

Como a IA e a aprendizaxe automática están facendo que o sector sanitario sexa máis centrado no paciente

कैसे AI और मशीन लर्निंग स्वास्थ्य सेवा क्षेत्र को अधिक रोगी-केंद्रित बना रहे हैं

AIと機械学習が医療分野をより患者中心に変える

AI жана машинаны үйрөнүү кантип саламаттыкты сактоо секторун сабырдуураак кылат

Ndenge nini AI mpe Machine Learning Ezali Kosala ete Secteur ya Soins de Santé ezala mingi na ba malades

Paano Ginagawa ng AI at Machine Learning ang Sektor ng Pangangalagang Pangkalusugan na Mas Nakasentro sa Pasyente

Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here.
Want to nominate a startup? Follow the steps here.Use the following sections to tell readers about your startup and get them to vote for you! These questions are designed to help tell readers about your company and vision and you do NOT need to answer all of them. Answer the ones that you feel can provide the most information.Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Wanna use this template? Click here. Hey Hackers![Insert your Startup name] has been nominated in HackerNoon’sStartups of The Year 2024 awards in [enter city name your startup is based], [country] under the Healthcare category. Please vote for us here: [insert URL to startup voting page for your city] [insert URL to startup voting page for your parent industry] [insert URL to startup voting page for your (3) sub industries] Read more about us below to understand why we deserve your vote. Meet [insert your startup name] Give us your elevator pitch
Share an image of your startup team, logo, product, etc. What Sets Your Startup Apart From Other Healthcare Startups? What makes your startup unique and stand out? What Have Been Your Proudest Accomplishments Thus Far? Time to brag! Let us know of your proudest achievements. What Lessons Have You Learned? What were some lessons learned from running your healthcare startup? Why Did You Decide to Participate in HackerNoon’s Startups of The Year Event? What Would It Mean For Your Startup if You Won? Let us know why you joined and what you hope to gain. What Future Plans Do You Have for Your Healthcare Startup? Where Do You See it in 3-4 Years? What do you envision for the future of your startup? How Has the Healthcare Sector Changed in Recent Years? How Do You Believe It Will Change in the Future? We want to hear about how your field has changed and how it will change in the future. Any Closing Words? Let the world know once more what your startup is all about and why they should vote for you in the 2024 Startups of The Year Awards. Vote for us today! [Insert link to startup voting page for your city, parent industry, or sub industry]. Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here. Want to nominate a startup? Follow the steps here. Use the following sections to tell readers about your startup and get them to vote for you! These questions are designed to help tell readers about your company and vision and you do NOT need to answer all of them. Answer the ones that you feel can provide the most information. Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here . Startups of The Year 2024 create a brand profile create a brand profile create a brand profile here here Want to nominate a startup? Follow the steps here . here here Use the following sections to tell readers about your startup and get them to vote for you! These questions are designed to help tell readers about your company and vision and you do NOT need to answer all of them. Answer the ones that you feel can provide the most information. you do NOT need to answer all of them. Answer the ones that you feel can provide the most information. Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here , here , and here . last year’s Startups of The Year interview questions last year’s Startups of The Year interview questions here here here here here here Wanna use this template? Click here. Wanna use this template? Click here . here Hey Hackers! [Insert your Startup name] has been nominated in HackerNoon’s Startups of The Year 2024 awards in [enter city name your startup is based], [country] under the Healthcare category. Startups of The Year 2024 awards Healthcare Please vote for us here: Please vote for us here: [insert URL to startup voting page for your city] [insert URL to startup voting page for your parent industry] [insert URL to startup voting page for your (3) sub industries] Read more about us below to understand why we deserve your vote. Meet [insert your startup name] Meet [insert your startup name] Give us your elevator pitch
Share an image of your startup team, logo, product, etc. Give us your elevator pitch Share an image of your startup team, logo, product, etc. Give us your elevator pitch Share an image of your startup team, logo, product, etc. What Sets Your Startup Apart From Other Healthcare Startups? What makes your startup unique and stand out? What makes your startup unique and stand out? What Have Been Your Proudest Accomplishments Thus Far? Time to brag! Let us know of your proudest achievements. Time to brag! Let us know of your proudest achievements. What Lessons Have You Learned? What were some lessons learned from running your healthcare startup? What were some lessons learned from running your healthcare startup? Why Did You Decide to Participate in HackerNoon’s Startups of The Year Event? What Would It Mean For Your Startup if You Won? Let us know why you joined and what you hope to gain. Let us know why you joined and what you hope to gain. What Future Plans Do You Have for Your Healthcare Startup? Where Do You See it in 3-4 Years? What do you envision for the future of your startup? What do you envision for the future of your startup? How Has the Healthcare Sector Changed in Recent Years? How Do You Believe It Will Change in the Future? We want to hear about how your field has changed and how it will change in the future. We want to hear about how your field has changed and how it will change in the future. Any Closing Words? Let the world know once more what your startup is all about and why they should vote for you in the 2024 Startups of The Year Awards. Let the world know once more what your startup is all about and why they should vote for you in the 2024 Startups of The Year Awards. Vote for us today! [Insert link to startup voting page for your city, parent industry, or sub industry]. Vote for us today! [Insert link to startup voting page for your city, parent industry, or sub industry].

Startups of the Year 2024: Healthcare Interview

Healthcare Tech, Healthcare - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Healthcare Tech startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Healthcare Tech industry. https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. The Startups in the Healthcare Tech industry nominated for Startups of The Year 2024 include: QUALITY HEALTHCARE CENTER
Your Cue
GUTolution
LonVi
HealingHand Tech
BioLinker
FoundationDx
Wassor Womanity
Lumena MindGym
Caare Foundation
Dimple Bindra
Mercurial AI
AGPHARM BIOINNOVATIONS LLP
PetPal PH
Secured Health
MedGos
Aicury
Biocell
Kobeesco
BetterSpace
Wuru
VitruvianMD
Glooma
STMPatch
CARÁ Health
Vuala
Forte Biotech - RAPID Aquaculture Diagnostics
Tenang AI
Alithea Bio
Mindcafe India “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st, and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. Visit our FAQ page to learn more. Download our design assets here. Check out the Startups of The Year Merch Shop here. HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool. Get your offer now! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free. Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Healthcare Tech, Healthcare - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Healthcare Tech startup ecosystem. Healthcare Tech, Healthcare - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Healthcare Tech startup ecosystem. Healthcare Tech , Healthcare Healthcare Tech - October 10, 2024 - October 10, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “ Startups of The Year ” award, featuring the most promising and innovative companies in the Startups of The Year startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Healthcare Tech industry. https://youtu.be/XOpG6B4AKPU?embedable=true https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in the Healthcare Tech industry here . here Startup of The Year in Startup of The Year in the Healthcare Tech industry here here The Startups in the Healthcare Tech industry nominated for Startups of The Year 2024 include: Startups in Startups in Startups in the Healthcare Tech industry the Healthcare Tech industry nominated QUALITY HEALTHCARE CENTER Your Cue GUTolution LonVi HealingHand Tech BioLinker FoundationDx Wassor Womanity Lumena MindGym Caare Foundation Dimple Bindra Mercurial AI AGPHARM BIOINNOVATIONS LLP PetPal PH Secured Health MedGos Aicury Biocell Kobeesco BetterSpace Wuru VitruvianMD Glooma STMPatch CARÁ Health Vuala Forte Biotech - RAPID Aquaculture Diagnostics Tenang AI Alithea Bio Mindcafe India QUALITY HEALTHCARE CENTER Your Cue GUTolution LonVi HealingHand Tech BioLinker FoundationDx Wassor Womanity Lumena MindGym Caare Foundation Dimple Bindra Mercurial AI AGPHARM BIOINNOVATIONS LLP PetPal PH Secured Health MedGos Aicury Biocell Kobeesco BetterSpace Wuru VitruvianMD Glooma STMPatch CARÁ Health Vuala Forte Biotech - RAPID Aquaculture Diagnostics Tenang AI Alithea Bio Mindcafe India “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the Healthcare Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO . “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” David Smooke, HackerNoon Founder & CEO Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st , and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Startups of The Year 2024 nominate their favorite startups until October 31st nominate their favorite startups Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. get free interviews startup-friendly packages startup-friendly packages Evergreen Tech Company News Evergreen Tech Company News In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Healthcare Tech industry here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in the Healthcare Tech industry here . here Startup of The Year in Startup of The Year in the Healthcare Tech industry here here About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. Startups of The Year 2024 Startups of The Year 2024 many stories many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview on HackerNoon Evergreen Tech Company News Evergreen Tech Company News Visit our FAQ page to learn more. FAQ FAQ Download our design assets here . here here Check out the Startups of The Year Merch Shop here . here here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. startup-friendly packages startup-friendly packages Meet our sponsors: Meet our sponsors: Meet our sponsors: Wellfound: Join the #1 global, startup-focused community . At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months , to build and scale your company with one powerful tool. Get your offer now ! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free . Hubspot: Get started for free Get started for free Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection , businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform AI end-to-end Search and Discovery Platform

Startups of the Year 2024: 5,508 Startups Nominated in the Healthcare Tech Industry

2024 maran qalltawinaka: 5.508 Qalltawinakaw Industria Tecnológica de Salud ukan sutinchata

Стартъпи на 2024 г.: 5 508 стартиращи фирми, номинирани в технологичната индустрия на здравеопазването

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स्टार्टअप्स ऑफ द ईयर 2024: हेल्थकेयर टेक इंडस्ट्री में 5,508 स्टार्टअप नामांकित

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2024年のスタートアップ・オブ・ザ・イヤー：ヘルスケア・テック業界で5,508社のスタートアップがノミネート

2024 жылдың стартаптары: денсаулық сақтау саласындағы 5 508 стартап ұсынылды

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