Modern Mobility Aids Welcomes Dr. Zakiuddin Ahmed as President; Revolutionizing healthcare through Telehealth BRAMPTON, Ontario,

Modern Mobility Aids Appoints Accomplished Industry Leader as New President

who are also members of the UOC eHealth Center's Behavioral Design Lab research group. The study, "Family Context Surrounding the Use of Technologies and Their Impact in Adolescents' Media Multitasking," was published online in 2021. It uses data collected ...

Study finds more than half of teenagers have no rules for using tech at home

KFHU has taken a significant leap forward in its pursuit of excellence by implementing TrakCare full clinical suite, patient administration system, and TrakCare Laboratory Enterprise® (TCLE), ushering in a new era of enhanced clinical services and improved patient safety.

King Fahad Hospital enhances patient care with InterSystems TrakCare

CSL, a leading Critical IoT Connectivity provider, and , specialists in the design and development of mission-critical communication,

CSL and GRC Announce Strategic Partnership to provide Satellite Connectivity for Critical National Infrastructure protection

Optical Suppliers Association autumn meeting focused on technology standardisation to deliver better patient outcomes. Simon Jones reports

In Focus: E-health initiative attracts new OSA members

Centre for eHealth and Wellbeing Research, Department of Psychology, Health & Technology, University of Twente, Enschede, Netherlands Background: There is a growing interest to support home-based dementia care via contactless monitoring (CM) technologies ...

Understanding acceptance of contactless monitoring technology in home-based dementia care: a cross-sectional survey study among informal caregivers

Airtel Africa’s Group CEO, Dr. Segun Ogunsanya has challenged the telecommunications industry in Africa to leverage emerging technologies to enable all people in the continent to connect, engage, and transact with the rest of the world.

Segun Ogunsanya Challenges Telcos to Leverage Emerging Technologies

while e-health can be used to improve patient monitoring and make health facilities more efficient.“The telecom industry is in a unique position to make it easier for people to enter the digital world by deploying these technologies. This is through ...

Airtel Africa CEO challenges telecom Industry to leverage on emerging technologies

Emerging technologies can be used in: AI-aided e-learning to design best curriculum based on students learning abilities; e-health to improve patient monitoring and more efficient health facilities; Agritech that uses AI and connectivity in crop disease ...

Airtel Africa Explains How Emerging Technologies can Drive Africa’s Digital, Financial Inclusion

Morial Convention Center in New Orleans, will feature the NSC Safety Technology Pavilion at Booth #2437, offering an educational glimpse into the future of safety technology. Open to attendees ...

NSC Safety Technology Pavilion Spotlights Emerging Technologies

Get the most recent info and news about eHealth Technologies™ on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

eHealth Technologies, a leading health care technology company that advances the delivery of life-altering care, serves over 100 of the nation’s top hospitals, including 17 of the top 20 U.S. News & World Report Honor Roll Hospitals. Since opening its doors in 2006, eHealth Technologies has helped 2.2 million patients receive prompt treatment for critical health needs, like cancer and organ transplant, by retrieving, organizing, and aggregating medical information, pathology reports, and images from disparate systems into a searchable digital medical record. eHealth Technologies also enabled access to over 27 million images for providers in 2021 alone, through the company’s nationwide Health Information Exchange services.

eHealth Technologies™

Meet the Winners of Startups in North and Central America

Authors:
(1) Prabath Jayatissa, University of Colombo
(2) Roshan Hewapathirane, University of Colombo Table of Links Abstract & Introduction Methodology Results Conclusion & References 4. CONCLUSION Interoperability among health information systems is crucial for improving healthcare delivery in low and middle-income countries (LMICs) where access to quality healthcare is often limited. However, achieving interoperability in LMICs faces challenges such as limited resources, fragmented health information systems, and diverse health IT infrastructure. Strategies such as standardisation, consolidation, investment in health IT infrastructure, capacity building, and addressing data privacy and security concerns can enhance interoperability efforts. Collaborative efforts among governments, non-profit organisations, the private sector, and other stakeholders are essential for overcoming challenges and promoting interoperability in LMICs. Further research is needed to evaluate the impact of these strategies and identify novel approaches that are specific to the unique challenges faced by different regions and contexts within LMICs. Research on the cost-effectiveness and sustainability of interoperable health information systems is also crucial. Significant challenges include the need for more standardisation, fragmented health information systems, limited resources, and data privacy concerns. However, strategies such as standardisation, consolidation, investment in health IT infrastructure, and capacity building can help overcome them. Collaborative efforts are needed to address the multifaceted challenges of interoperability in LMICs and implement effective strategies. Further research and collaborative efforts are required to address the unique needs and contexts of LMICs and unlock the potential of health information systems to improve healthcare outcomes and advance health systems towards more integrated, patient-centred, and data-driven care in LMICs. REFERENCES [1] Adler-Milstein, J., DesRoches, C. M., Kralovec, P., Foster, G., Worzala, C., Charles, D., & Searcy, T. (2013). Electronic health record adoption in US hospitals: progress continues, but challenges persist. Health Affairs, 32(8), 1478-1485. [2] Adefioye, O. A., Adeleke, I. T., & Adewumi, A. O. (2019). Interoperability of health information systems in low-income countries: a systematic review of barriers and facilitators. BMC Medical Informatics and Decision Making, 19(1), 16. [3] Blaya, J. A., Fraser, H. S., & Holt, B. (2017). E-health technologies show promise in developing countries. Health Affairs, 36(12), 2168-2175. [4] Braa, J., Sahay, S., & Westerlund, M. (2017). The role of participatory design in strengthening community-based health information systems: a case study from Mozambique. Health Informatics Journal, 23(3), 180-189. [5] Kamadjeu, R. (2019). Impact of interoperability among electronic health records in low-resource settings: A systematic review. International Journal of Medical Informatics, 123, 27-34. [6] Karim, A. M., Ahsan, H., & Uddin, M. J. (2019). Interoperability in e-Health: A Systematic Literature Review. Health and Technology, 9(4), 687-697. [7] Seebregts, C. J., Mamlin, B. W., Biondich, P. G., Fraser, H. S., & Wolfe, B. A. (2017). Human factor considerations in developing and implementing information and communication technologies for health in low-resource settings. Yearbook of Medical Informatics, 26(01), 123-130. [8] Sharma, A., Wickramasinghe, N., & Gupta, D. (2017). Leveraging the capabilities of electronic health records for enhancing decision-making processes in low-resource settings: a literature review. Health Informatics Journal, 23(2), 89-99. [9] W G P T Jayatissa, Vajira HWD, Roshan H. Review of Master Patient Index. Dent Res Int J DRIJ. 2017;3(2):37–48. https://arxiv.org/abs/1803.00451 [10] Tchouaket, É. N., Charrier, R., & Henry, S. (2019). Addressing the lack of interoperability among health information systems in low-income countries: a socio-technical approach. Health and Technology, 9(5), 729-742. [11] Blaya, J.A., Fraser, H.S.F., Holt, B. (2017). E-health interoperability. In: Marschollek, M., Bauer, A., Wolf, K.H., Gradinger, M., eds. eHealth2016 - Health Informatics Meets eHealth: From Sensors to Decisions. IOS Press, pp. 9-14. [12] Tchouaket, É.N., Moine, M.P., Adedokun, A., et al. (2019). Challenges to Interoperability of Health Information Systems in Low- and Middle-Income Countries: A Literature Review. Studies in Health Technology and Informatics, 264, pp. 1399-1403. [13] Adler-Milstein, J., Jha, A.K. (2013). Sharing Clinical Data Electronically: A Critical Challenge for Fixing the Health Care System. JAMA, 309(10), pp. 991-992. [14] Kamadjeu, R. (2019). Challenges of Implementing eHealth in Developing Countries: An Example of a Web-Based Asynchronous Telemedicine System. Health Informatics Journal, 25(1), pp. 62-71. [15] Sharma, A., Kamadjeu, R., Mirza, S., et al. (2017). Development of a National Health Information System in a Resource-Limited Setting: A Case Study from Liberia. Health Informatics Journal, 23(4), pp. 295-306. [16] Jayatissa P, Vajira HWD, Roshan H. Developing a functional prototype Master Patient Index (MPI) for interoperability of E-Health systems in Seri Lanka. Dent Res Int J DRIJ. 2017;2(2):9–26. https://arxiv.org/abs/1803.00451 [17] Seebregts, C.J., Mamlin, B.W., Biondich, P.G., et al. (2017). The OpenMRS Implementers Network. International Journal of Medical Informatics, 108, pp. 117-121. [18] Adefioye, O.A., Asaolu, I.O., Ajayi, T.A., et al. (2019). Ethical and Legal Issues in Health Information Exchange in Low and Middle Income Countries: A Systematic Review. BMC Medical Ethics, 20(1), pp. 84. [19] Braa, J., Hanseth, O., Mohammed, W., et al. (2017). Developing Health Information Systems in Developing Countries: The Flexible Standards Strategy. MIS Quarterly, 41(1), pp. 309-322. [20] Karim, A.M., Nematzadeh, A., Gombera, F., et al. (2019). eHealth in Low- and Middle-Income Countries: Findings from the Center for Health Market Innovations. Health Affairs, 38(5), pp. 711- 718. [21] Jayatissa P, Hewapatirane R. Development of Minimum Clinical Data Set For Master Patient Index(MPI) for Sri Lankan Context. https://airccse.com/drij/papers/4422drij01.pdf .2022 Nov 1;4(4):1–18. This paper is available on arxiv under CC 4.0 license. Authors: (1) Prabath Jayatissa, University of Colombo (2) Roshan Hewapathirane, University of Colombo Authors: Authors: (1) Prabath Jayatissa, University of Colombo (2) Roshan Hewapathirane, University of Colombo Table of Links Abstract & Introduction Abstract & Introduction Methodology Methodology Results Results Conclusion & References Conclusion & References 4. CONCLUSION Interoperability among health information systems is crucial for improving healthcare delivery in low and middle-income countries (LMICs) where access to quality healthcare is often limited. However, achieving interoperability in LMICs faces challenges such as limited resources, fragmented health information systems, and diverse health IT infrastructure. Strategies such as standardisation, consolidation, investment in health IT infrastructure, capacity building, and addressing data privacy and security concerns can enhance interoperability efforts. Collaborative efforts among governments, non-profit organisations, the private sector, and other stakeholders are essential for overcoming challenges and promoting interoperability in LMICs. Further research is needed to evaluate the impact of these strategies and identify novel approaches that are specific to the unique challenges faced by different regions and contexts within LMICs. Research on the cost-effectiveness and sustainability of interoperable health information systems is also crucial. Significant challenges include the need for more standardisation, fragmented health information systems, limited resources, and data privacy concerns. However, strategies such as standardisation, consolidation, investment in health IT infrastructure, and capacity building can help overcome them. Collaborative efforts are needed to address the multifaceted challenges of interoperability in LMICs and implement effective strategies. Further research and collaborative efforts are required to address the unique needs and contexts of LMICs and unlock the potential of health information systems to improve healthcare outcomes and advance health systems towards more integrated, patient-centred, and data-driven care in LMICs. REFERENCES [1] Adler-Milstein, J., DesRoches, C. M., Kralovec, P., Foster, G., Worzala, C., Charles, D., & Searcy, T. (2013). Electronic health record adoption in US hospitals: progress continues, but challenges persist. Health Affairs, 32(8), 1478-1485. [2] Adefioye, O. A., Adeleke, I. T., & Adewumi, A. O. (2019). Interoperability of health information systems in low-income countries: a systematic review of barriers and facilitators. BMC Medical Informatics and Decision Making, 19(1), 16. [3] Blaya, J. A., Fraser, H. S., & Holt, B. (2017). E-health technologies show promise in developing countries. Health Affairs, 36(12), 2168-2175. [4] Braa, J., Sahay, S., & Westerlund, M. (2017). The role of participatory design in strengthening community-based health information systems: a case study from Mozambique. Health Informatics Journal, 23(3), 180-189. [5] Kamadjeu, R. (2019). Impact of interoperability among electronic health records in low-resource settings: A systematic review. International Journal of Medical Informatics, 123, 27-34. [6] Karim, A. M., Ahsan, H., & Uddin, M. J. (2019). Interoperability in e-Health: A Systematic Literature Review. Health and Technology, 9(4), 687-697. [7] Seebregts, C. J., Mamlin, B. W., Biondich, P. G., Fraser, H. S., & Wolfe, B. A. (2017). Human factor considerations in developing and implementing information and communication technologies for health in low-resource settings. Yearbook of Medical Informatics, 26(01), 123-130. [8] Sharma, A., Wickramasinghe, N., & Gupta, D. (2017). Leveraging the capabilities of electronic health records for enhancing decision-making processes in low-resource settings: a literature review. Health Informatics Journal, 23(2), 89-99. [9] W G P T Jayatissa, Vajira HWD, Roshan H. Review of Master Patient Index. Dent Res Int J DRIJ. 2017;3(2):37–48. https://arxiv.org/abs/1803.00451 [10] Tchouaket, É. N., Charrier, R., & Henry, S. (2019). Addressing the lack of interoperability among health information systems in low-income countries: a socio-technical approach. Health and Technology, 9(5), 729-742. [11] Blaya, J.A., Fraser, H.S.F., Holt, B. (2017). E-health interoperability. In: Marschollek, M., Bauer, A., Wolf, K.H., Gradinger, M., eds. eHealth2016 - Health Informatics Meets eHealth: From Sensors to Decisions. IOS Press, pp. 9-14. [12] Tchouaket, É.N., Moine, M.P., Adedokun, A., et al. (2019). Challenges to Interoperability of Health Information Systems in Low- and Middle-Income Countries: A Literature Review. Studies in Health Technology and Informatics, 264, pp. 1399-1403. [13] Adler-Milstein, J., Jha, A.K. (2013). Sharing Clinical Data Electronically: A Critical Challenge for Fixing the Health Care System. JAMA, 309(10), pp. 991-992. [14] Kamadjeu, R. (2019). Challenges of Implementing eHealth in Developing Countries: An Example of a Web-Based Asynchronous Telemedicine System. Health Informatics Journal, 25(1), pp. 62-71. [15] Sharma, A., Kamadjeu, R., Mirza, S., et al. (2017). Development of a National Health Information System in a Resource-Limited Setting: A Case Study from Liberia. Health Informatics Journal, 23(4), pp. 295-306. [16] Jayatissa P, Vajira HWD, Roshan H. Developing a functional prototype Master Patient Index (MPI) for interoperability of E-Health systems in Seri Lanka. Dent Res Int J DRIJ. 2017;2(2):9–26. https://arxiv.org/abs/1803.00451 [17] Seebregts, C.J., Mamlin, B.W., Biondich, P.G., et al. (2017). The OpenMRS Implementers Network. International Journal of Medical Informatics, 108, pp. 117-121. [18] Adefioye, O.A., Asaolu, I.O., Ajayi, T.A., et al. (2019). Ethical and Legal Issues in Health Information Exchange in Low and Middle Income Countries: A Systematic Review. BMC Medical Ethics, 20(1), pp. 84. [19] Braa, J., Hanseth, O., Mohammed, W., et al. (2017). Developing Health Information Systems in Developing Countries: The Flexible Standards Strategy. MIS Quarterly, 41(1), pp. 309-322. [20] Karim, A.M., Nematzadeh, A., Gombera, F., et al. (2019). eHealth in Low- and Middle-Income Countries: Findings from the Center for Health Market Innovations. Health Affairs, 38(5), pp. 711- 718. [21] Jayatissa P, Hewapatirane R. Development of Minimum Clinical Data Set For Master Patient Index(MPI) for Sri Lankan Context. https://airccse.com/drij/papers/4422drij01.pdf .2022 Nov 1;4(4):1–18. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Enhancing Interoperability in LMIC Healthcare Information Systems

Medical Software Testing 101: Advice to Consider for Upgrading Patient Experiences 

Systems Interoperability Types: A Tertiary Study: Discussing the Results and What Comes Next

Every individual does their best to live a healthy life in their little way. Whether it be eating right, or maintaining proper hygiene. There is a constant struggle to balance that process but there seem to be a lot of things that hinder it. Some of these include pollution, economic stability, education access and quality, health care access and quality, and societal or neighborhood environment. All these pose a threat to an individual's healthy lifestyle, especially that of the social environment, although it is not the only aspect to look out for. Nevertheless, because it is usually overlooked, we must take note of it, as it is likely to negatively affect a person's health by leading to obesity, food poisoning, mental health issues and even higher risk of diseases. However, the technology methods and apps encourage healthier behavior in individuals and help health care personnel with the proactive management of a healthy lifestyle in people. Technological advancements like , have given rise to easy detection and diagnosis, quick decision making and treatment. Artificial Intelligence (AI) Notwithstanding, the has more influence on people than other factors, the reason being that it has to do with the way of life and relationship of an individual. That is, the environment such a person lives in, the person's occupation and income status, the level of education one has or perhaps the resources such a person has to access. social environment That is why people on the lower part of the social ladder are twice as likely to acquire a health condition. Also, a poor social environment can make an individual feel anxious, confused and stressed. What process does technology enhance a healthy lifestyle? The 21st century has created various solutions for the health industry whereby several technologies have been developed to assist the enhancement of the health of an individual. There is no doubt that the impact of technological advancement from cloud computing to artificial intelligence on our lives, in this century is rapidly becoming inevitable. Is it the internet that has become so vast? Or the evolving technologies like the Internet of Things(IoT)? Or even our phones, which we use to pass information to one another, and get in touch with our friends and family far and wide? The impact of technology is too numerous to count that people also use it to manage their health, otherwise known as eHealth, which is the use of information and communication technology(ICT) to benefit the healthcare and wellbeing of people. Hence, what type of technology can we use to improve our healthy lifestyle and healthcare in general? 1. Apps Apps are developed for a vast number of services like enjoyment (games), getting in touch with people (social media), and also assistance in making things easier and faster. There is no disagreement with the fact that have their importance in the healthcare industry which has been made possible by developers. apps The involvement of some technology like cloud computing, artificial intelligence (AI) and augmented reality (AR), makes it complex for developers. Nevertheless, the use of these six phases; strategize, plan, analyze and design, app development, test and deploy, help them in mobile app development. Individuals have used an app for their mental, physical or emotional health at least once. Some apps have been developed to help you to know in detail what your healthcare expert is talking about. This helps to tackle the problem that comes with engagement between the doctor and the patient, setting reminders and many more. 2. Wearable Devices These are devices that you can wear on your wrist or body or even attach to a piece of clothing. These belong to different categories, such as fitness, sport, health, and entertainment. Concerning the advancement of Artificial Intelligence (AI) and the Internet of Things(IoT), developers involved in software development, have implemented the current account of wearable devices in health care to function as an integrated electronic health record system. wearable devices Instances of some refined wearable technology include a holographic computer in the form of virtual reality (VR) headset, artificial intelligence (AI) hearing aids, Google Glass and Microsoft's HoloLens, to track your health progress or physical activity. In most cases, they are paired with your mobile phone or a website to track and reserve the real-time data collected. You might have seen people wearing devices like smartwatches. Well, they are technologies that are linked to apps for monitoring your health in terms of sleep, and heart rate while worn. The data collected for the day, week or month gives you insight into your health track, feedback, along with tips for becoming healthier, which can be shared with a health care provider. 3. Air Purifiers are technology products that can disinfect the air by removing allergens, toxins, viruses, bacteria and pollutants. They are different from essential oil diffusers and humidifiers, which on the other hand, add particles to indoor air. Air purifiers Also, an air purifier will not likely remove or neutralize all particles in your home or environment, unlike a filter. This is because many particles can stay on soft surfaces, such as furniture, bedding, and floor, as well as hard surfaces, such as your walls but it is possible to sanitize the pollutants. Thus, the innovation and advancement of technology have brought about the AI-based purification system and the HEPA filter. The application of these technologies into air purifiers would help in filtering the air. Developers have integrated built-in sensors, computing algorithms, and an advanced DC motor that maximizes the temperature of healthy breathable air in your home or environment and can sharply adjust to meet your uniqueness. Also, the AI system in the air purifier can connect to the internet via a Wi-Fi network for providing accurate air quality analysis. Health personnel have advised doctors' offices, dentist offices, exam rooms, and any area that has a high concentration of contaminants in the air and is frequented by people to have air purifiers. According to research, this action is said to decrease the spread of illnesses and reduce airborne and surface pollutants, germs and contaminants. Nevertheless, research shows that air purifiers work best with a filter by sanitizing and filtering the air. In other words, an air purifier works with a high-efficiency particulate air (HEPA) filter and an Ultraviolet Light (UVC) whose function is to filter the air by trapping airborne pollutants, removing harmful particles and smoke in the area and also reducing the humidity level indoors. In Conclusion The process of has been made easy through technology. The health industry just as other industries have benefitted massively from the use of technology which on its end keeps evolving and getting better. enhancing a healthy lifestyle In other words, just as big data and IoT have been equipping the healthcare industry, AI and robotics have also been giving numerous potentials more efficiently than humans. The health industry does not doubt its new methods of working, even the technologies designed to keep us healthy, as every area of our lives has been impacted. It is important that we individuals have the right attitude to living a healthy lifestyle as that would make the effect and usage of technology easier and faster.

The Technological Process of Enhancing a Healthy Lifestyle

Having faced the global crisis, countries are only starting to trailblaze the path toward normalcy. Although an epidemiological endpoint is still out of reach, organizations are preparing for the ‘next normal’ and embracing novel strategies to gain a competitive edge and accelerate productivity. For that, companies modified their businesses once and for all through and delivering more goods and services online. Statista mentions that by 2024, the on DT will double in comparison with 2020 and comprise $2.39 trillion!\ digital transformation (DT) global spending However, any changes are challenging, and digital ones are even more challenging. Organizations still struggle with implementing highly complicated solutions with AI, IoT, AR/VR, blockchain, or other modern technologies at the core. To ride the wave of innovation and companies may focus their efforts on quality assurance. But what QA tendencies to consider in 2022 to build an effective testing process and gain a competitive edge? attain boosted productivity and quality at speed, In the article, we will cover the top 5 software testing trends that will influence industry development in the years ahead and help businesses mitigate the COVID-19 aftermath. #1 – Continuous evolution of Agile and DevOps methodologies Organizations now are adjusting themselves to the post-pandemic era, and this process is characterized by the growing stake in introducing innovations and fit-for-purpose approaches. For instance, we’ve already observed in the shift to the tailored to help organizations deliver good-to-go code with built-in security from the get-go. Others infuse into their CI/CD pipelines, making QA a major function in the software development process. the uptick DevSecOps culture QAOps However, adopting novel practices inevitably means the rising need for a right-skilled talent pipeline. It is here when an issue of great concern arises. According to the World Quality Report 2021-22 (WQR), 44% of survey participants experience while another 31% stated that they face a gap in the shortage of expertise of agile testing teams, test environment, containerization, and test data skills. When it comes to easing the process of embedding in-demand methodologies and simultaneously optimizing their testing strategies, businesses can do the following: Shift QA activities left to care about software quality and prevent issues early in SDLC Rely on automated testing to build, test, and ship IT products faster Leverage AI to enable optimization of test cases Apply smart online dashboards to ensure end-to-end quality monitoring in real time. However, the most important recipe for success features the need to focus on as well as develop the ability business requirements and organizational culture, to embrace change. Why is sticking to Agile and DevOps so significant for companies today? When implemented right, these methodologies can save the day. Almost two-thirds of IT business representatives mentioned that they managed to boost productivity, software quality, delivery velocity, and the cost of quality. #2 – Quality engineering (QE) as a major function in digital transformation support COVID-19 pandemic has expedited the adoption of digital technologies worldwide. Global by Statista indicates that an overwhelming of respondents admitted a boost in DT processes velocity in their companies, while 68% assumed that DT speed was impressive. research 97% To handle increased demand in remote work and ensure business continuity, companies had to accelerate the digitization of supply chain interactions and significantly enlarge the number of digitally-driven solutions. This is no surprise when — improved productivity and efficiency, enhanced CX, polished quality, better organizational agility and flexibility, decreased expenses. There are even more benefits on the agenda. considering the outcomes However, the path to digital adoption is hard. Companies must embrace novel technologies and approaches like How to do it right, ensure high IT product quality, and mitigate cybersecurity and data privacy risks? 5G, edge computing, AI, IoT, intelligent automation, embedded software… Organizations may support software releases with QE. Focused on defect prevention and high velocity, it helps embed quality into the entire development process to reach seamless software operation and engaging user experience. While doing so, businesses have already marked QE engineers should possess in the future to cope with sophisticated tasks — cloud computing, cybersecurity, big data and analytics (WQR). must-have skills Nevertheless, the pace of change will likely slow down, and it’s great that despite facing novel challenges, companies are doing their utmost to ensure the impeccable operation of smart digital environments. #3 – AI and ML to attain a smart testing approach According to Statista, in North America alone, the profit from the AI software market will and comprise $50 billion by 2025. skyrocket From accounting and HR to digital marketing and travel industry, AI is making its way to disrupting business environments and boosting organizational capabilities. And software testing industry is no exception. The WQR highlights that in the future, we’ll witness the increasing implementation of this technology to strengthen the QA efforts, for instance, test automation. AI will expedite testing time and improve quality due to eliminating the human intervention factor. In this regard, Gartner states that by 2023, of infrastructure and operations teams in large-sized companies will give preference to AI-augmented automation for the sake of improving organizational efficiency. Used to develop and maintain automated scripts as well as enable scriptless automation and self-healing, 40% in software testing will also continue to constitute mature trends in the years to come. Eliminating excessive test cases within a suite, predicting issues in test models, test prioritization, and AI-driven analytics Although and associated with test strategy and test design, setup and generation of test data, bias and ethical validation in AI, and some others still exist, already today, more and more companies leverage this mighty innovation skill gaps needed from QE experts to improve the accuracy of testing results, enhance overall software quality, and decrease time to market. #4 – Intelligent automation to get faster business outcomes Test automation implementation will keep gaining momentum in the years ahead. Not surprising due to its multiple benefits — from better defects detection to reduced test cycle time. For example, within the WQR report, half of 1,750 of the interviewed IT leaders asserted that their test automation efforts are paying off, while almost 70% marked improved control and transparency of QA activities. It’s been rather challenging for organizations (e.g., with AI/ML or test automation architecture skills). However, businesses across diverse industries increase test automation adoption levels and gradually to engage the right-skilled specialists enlarge the scope of automation techniques in use. So, in the future, we may face a growth in the application of: to significantly streamline test activities and decrease human intervention Robotic process automation (RPA) to maximize reuse and minimize the need for hand-coding A scriptless (no-/low-code) approach to automation to provide tests with the ability to automatically update themselves to avoid failure if the function has changed Self-healing automation to extend testing coverage, boost velocity and performance by fulfilling more tests in a real browser environment Headless automation to briskly find and compile the right data for each test, enabling a less resource-intensive testing process. Automation of test data However, to bear fruit from intelligent test automation adoption and maintenance, companies should always remember a cardinal rule — aligning processes to unique business needs. #5 – IoT testing to support the operation of interconnected devices Statista again shares quite impressive data and valuable insights — the worldwide amount of will rise to 25.4 billion in 2030, while will grow from $389 billion in 2020 to $1 trillion! IoT devices IoT annual global revenue By representing the network of devices that communicate with one another and share data, IoT brings to the table multiple like efficient operation management, work safety improvements, reduced human labor, and many others. business benefits Moreover, the uptick in the adoption of a constantly connected has made this innovation one of the pivotal technologies for businesses in the years ahead. 5G technology, the boom in DT, IoT sensors usage in eHealth to fight the pandemic Noteworthy is the IoT role in the emergence of which have seen an increase in popularity. Just imagine: China alone is deploying approximately across the country. While Statista predicts that the for smart city technologies, products, and services will attain $129 billion this year. smart cities, 800 smart city programs worldwide revenue Keeping on the subject — Singapore, Dubai, and Oslo are great examples of the most impactful growing smart cities today, From connected vehicles and smart waste management solutions to smart air quality monitors and grids, their potential is almost limitless, with IoT at the core of their operation. ensuring their citizens a higher quality lifestyle. This is why comprehensive IoT testing should become a part of the software creation process. And a special emphasis should be placed on as the devices are connected to the Internet, which increases the probability of fraudulent attacks. IoT focused on verifying all possible combinations of devices and sensors will help spot vulnerabilities and system flaws. cybersecurity penetration testing Other high-priority testing types include functional, performance, compatibility, usability testing, test automation all aimed at and improving the quality of IoT-enabled networks. eliminating interoperability challenges The increased role of quality assurance COVID-19 is the problem we’ll all have to live with for the long haul. Luckily, businesses accelerated digital transformation pace, agile mindsets, and willingness to adopt innovations are among them. have shown the signs of successful adaptation to a briskly changing situation — However, digital adoption is challenging, requiring a whole set of professional skills and timely QA support. Open-minded companies have become more aware of software quality importance and may focus on the defining QA trends that will rule the industry in the upcoming year. Among them, it’s possible to highlight: The continuous popularity of Agile and DevOps QE as a means to support digital transformation The use of AI and ML to test smartly Automation to get faster business outcomes IoT testing to ensure swift operation of interconnected devices. By sticking to the technology-driven strategy with quality assurance at the helm, businesses can increase organizational performance and expedite the delivery time of quality software, so requisite in the post-pandemic world.

What the future holds: 5 core QA trends to rule 2022

HackerNoon Reporter: Please tell us briefly about your  background. Growing up in the time of the Soviet Union I went to a strong math school, I was always passionate about programming. I was fascinated by innovation, research, and industrial programming; сreating smart algorithms to solve real-world problems. During my third year at the university, I went to work at an IT programming lab where I made my first steps studying ontologies and creating learning management systems. We did a project for a client that was at the forefront of innovation in Russia. As it turns out, this was the place where I met my future business partners. I realize now that we were brought together by this drive for innovation and desire to put our brains into something big and meaningful. What's your startup called? And in a sentence or two, what does it do? ENBISYS is a growing IT company and we have several owned startups and spin-offs of our own. We focus on сustom software development, machine learning research, adaptive learning systems, and medical imaging diagnostic platforms. What is the origin story? In the beginning, we were just five guys working on one project for a single client in healthcare. Then, they spread the word and another customer came in. Our clients from Europe appreciated working with talented programmers. We started building a network and gradually learned everything about leading a business in IT. What do you love about your team, and why are you the ones to solve this problem? ENBISYS team consists of the best professionals with a great attitude for their work. All of them are committed to their projects and have a good cultural fit for clients from different countries, as well as communication and soft skills. The orchestrated effort of each team member allows ENBISYS to solve the most ambitious challenges for our clients. If you weren’t building your startup, what would you be doing? I am into gaming, so if I ever consider doing something different than leading an innovative business, I will choose to join a cybersport team and compete with the most experienced gamers! At the moment, how do you measure success? What are your core metrics? First of all, it is my team that inspires me to reach the most ambitious goals. Second is my own resourcefulness and well-being that helps me to perform at my best. The third is the exponential growth of the company’s profit. What’s most exciting about your traction to date? The IT industry is changing rapidly, always offering numerous challenges and opportunities to solve. I am excited by new technologies and approaches and the leap they may make in enhancing people’s quality of life through digitalization that will inevitably take place. What technologies are you currently most excited about, and most worried about? And why? The technologies that fascinate me are Artificial Intelligence, Machine Learning, and Quantum Computing: they will help humanity reduce routine processes and enhance their quality. I am not worried about robots or AI taking over people’s jobs because creativity and innovative thinking are very difficult to automate. What drew you to get published on HackerNoon? What do you like most about our platform? Within our content strategy at ENBISYS, we always look for opportunities to share our expertise with the audience who might need it. It was a surprise for us to get listed as a nominee on Startup of the Year, so after exploring the platform we understood that we would like to contribute to your community knowledge base with our vision on digitalization, eHealth, EdTech, and other subjects of expertise. What advice would you give to the 21-year-old version of yourself? Try to check hypotheses faster, since not every hypothesis is both suitable for business and can bring value to people. What is something surprising you've learned this year that your contemporaries would benefit from knowing? Every unexpected event like lockdown or crisis is challenging on the one hand and creates opportunities on the other hand. For example, Telemedicine and EdTech apps have grown dramatically and gained popularity during lockdown times, and this was a great chance to show people the convenience of using such services. Always look for opportunities the situation may bring! ENBISYS is nominated as a . Go vote! startup of the year in Tomsk

Startup Interview with Dmitry Bubnov, CEO Of ENBISYS

Hey everyone! and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon or my personal website . In today’s article, we’ll be looking at how to develop a RAG using Microsoft’s Semantic Kernel. , I’m Nataraj 100 days of AI here here Retrieval augmented generation (RAG) is one of the most common application that is being developed using different LLMs. We have previously explored how to develop a RAG using . In this post we will create a RAG using . langchain Microsoft’s Semantic Kernel To follow along, you will need the Open AI API. Step 1: Initialize Semantic Kernel The first step is to initialize semantic kernel and tell the kernel that we want to use Open AI’s chat completion and Open AI’s embedding model which we will later use to create embeddings. We will also tell the kernel that we want to use a memory store which will be Chroma DB in our case. Note that we are also instructing the Kernel that this memory store needs to be persistent. kernel = sk.Kernel()

kernel.add_text_completion_service("openai", OpenAIChatCompletion("gpt-4",api_key))

kernel.add_text_embedding_generation_service("openai-embedding", OpenAITextEmbedding("text-embedding-ada-002", api_key))

# chrome db
kernel.register_memory_store(memory_store=ChromaMemoryStore(persist_directory='mymemories2'))

print("Made two new services attached to the kernel and made a Chroma memory store that's persistent.") Step 2 – Create Embeddings In this example, we are creating a RAG that can answer questions on a SWOT analysis that we created for a pizza business. So in order to do that we take the SWOT analysis and get the embeddings for them and store the corresponding embeddings in a collection called “SWOT” in the persistent datastore that we created in the last step. strength_questions = ["What unique recipes or ingredients does the pizza shop use?","What are the skills and experience of the staff?","Does the pizza shop have a strong reputation in the local area?","Are there any unique features of the shop or its location that attract customers?", "Does the pizza shop have a strong reputation in the local area?", "Are there any unique features of the shop or its location that attract customers?"]
weakness_questions = ["What are the operational challenges of the pizza shop? (e.g., slow service, high staff turnover)","Are there financial constraints that limit growth or improvements?","Are there any gaps in the product offering?","Are there customer complaints or negative reviews that need to be addressed?"]
opportunities_questions = ["Is there potential for new products or services (e.g., catering, delivery)?","Are there under-served customer segments or market areas?","Can new technologies or systems enhance the business operations?","Are there partnerships or local events that can be leveraged for marketing?"]
threats_questions = ["Who are the major competitors and what are they offering?","Are there potential negative impacts due to changes in the local area (e.g., construction, closure of nearby businesses)?","Are there economic or industry trends that could impact the business negatively (e.g., increased ingredient costs)?","Is there any risk due to changes in regulations or legislation (e.g., health and safety, employment)?"]

strengths = [ "Unique garlic pizza recipe that wins top awards","Owner trained in Sicily at some of the best pizzerias","Strong local reputation","Prime location on university campus" ]
weaknesses = [ "High staff turnover","Floods in the area damaged the seating areas that are in need of repair","Absence of popular calzones from menu","Negative reviews from younger demographic for lack of hip ingredients" ]
opportunities = [ "Untapped catering potential","Growing local tech startup community","Unexplored online presence and order capabilities","Upcoming annual food fair" ]
threats = [ "Competition from cheaper pizza businesses nearby","There's nearby street construction that will impact foot traffic","Rising cost of cheese will increase the cost of pizzas","No immediate local regulatory changes but it's election season" ]

print("✅ SWOT analysis for the pizza shop is resident in native memory")

memoryCollectionName = "SWOT"

# lets put these in memory / vector store
async def run_storeinmemory_async():
    for i in range(len(strengths)):
        await kernel.memory.save_information_async(memoryCollectionName, id=f"strength-{i}", text=f"Internal business strength (S in SWOT) that makes customers happy and satisfied Q&A: Q: {strength_questions[i]} A: {strengths[i]}")
    for i in range(len(weaknesses)):
        await kernel.memory.save_information_async(memoryCollectionName, id=f"weakness-{i}", text=f"Internal business weakness (W in SWOT) that makes customers unhappy and dissatisfied Q&A: Q: {weakness_questions[i]} A: {weaknesses[i]}")
    for i in range(len(opportunities)):
        await kernel.memory.save_information_async(memoryCollectionName, id=f"opportunity-{i}", text=f"External opportunity (O in SWOT) for the business to gain entirely new customers Q&A: Q: {opportunities_questions[i]} A: {opportunities[i]}")
    for i in range(len(threats)):
        await kernel.memory.save_information_async(memoryCollectionName, id=f"threat-{i}", text=f"External threat (T in SWOT) to the business that impacts its survival Q&A: Q: {threats_questions[i]} A: {threats[i]}")

asyncio.run(run_storeinmemory_async())

print("😶‍🌫️ Embeddings for SWOT have been generated and stored in vector db") Step 3 – Ask your question Now that we have the embeddings of our data stored in the chrome vector store, we can ask questions related to the pizza business and get an answer. #ask questions on swot
potential_question = "What are the easiest ways to make more money?"
counter = 0

async def run_askquestions_async():
    memories = await kernel.memory.search_async(memoryCollectionName, potential_question, limit=5, min_relevance_score=0.5)
    display(f"### ❓ Potential question: {potential_question}")
    for memory in memories:
        if counter == 0:
            related_memory = memory.text
        counter += 1
        print(f"  > 🧲 Similarity result {counter}:\n  >> ID: {memory.id}\n  Text: {memory.text}  Relevance: {memory.relevance}\n")

asyncio.run(run_askquestions_async()) This is a grossly simplified version of how a RAG can be created using Semantic Kernel. The most popular choice of framework to build right now using LLMs is langchain and we have previously seen how to build a RAG using langchain. Although Langchain is more popular as we see more and more companies building tools, there will be more sophisticated tools out there and I have found that Semantic Kernel has a few special features that make it stand out. That’s it for Day 18 of 100 Days of AI. I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, . subscribe to it Follow me on , or for latest updates on 100 days of AI or . If you are in tech you might be interested in joining my community of tech professionals . Twitter LinkedIn HackerNoon bookmark this page here

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EHEALTH TECHNOLOGIES™

ehealthtechnologies.com

201-500 employees

Since 2006

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EHEALTH TECHNOLOGIES™

EVERGREEN INDEX #4416

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