Included Health is a new kind of healthcare company, delivering integrated virtual care and navigation

Included Health

User experiences with web and mobile applications are more important than ever. Users have high expectations for performance and demand consistent updates with new features and content. Thanks to low switching costs and a growing plethora of options available on the market, if users see even the smallest issue with stability, speed, or responsiveness, they’ll explore other options. Stability: A Barometer of Quality and Quantity Stability measures application health as well as user experience. It’s calculated in two main ways to provide insight. A percentage of Crash-free application sessions (or unhandled exceptions) Daily active users who do not experience an error Our insights help you determine application stability SLAs and SLOs, like how infrastructure and operational teams rely on the “five nines” to measure uptime and availability. Target stability scores best represent your SLO. This score can be thought of as an aspirational goal to balance fixing bugs with building new features. If your stability score is above target stability, you can focus on building new features. If lower, get the bugs. On the other hand, you can compare our critical stability score to your SLA. This is the minimum threshold your app should run on to ensure its functionality. If your stability score drops below your critical stability threshold, drop everything and focus on fixing bugs immediately. To help you compare your application to other leading web and mobile apps, Bugsnag has aggregated data to analyze stability trends and release frequency with industry benchmarks. We welcome you to learn from them as well. is a percentage of app sessions that are crash-free. Stability scores are used to gauge app health and user experience. Stability Measuring App Quality Across Industries When it comes to measuring app quality, stability hits different industries in varied ways. Factors like value of user interactions, and volume. Understanding these factors will help engineering organizations develop strategies for delivering higher quality apps. How Stability Turns Loyalty Into Revenue High Stability : Setting the bar while delivering enriching new experiences Trendsetters Media and Entertainment has taken off in the past several years when it comes to streaming media. As many newcomers attempt to grow their users, it remains essential for them to provide an optimal, uninterrupted experience. Meanwhile, to retain their massive subscriber base against increased competition, streaming giants seek to strike a balance between delivering a seamless experience and consistently offering new features to enhance their application – across a range of devices. Ecommerce continues to be a driving force even as brick and mortar retail attempts to recover to pre-pandemic levels. As worldwide ecommerce revenue expects to climb past $5.5 trillion in 2022, there’s a lot of money in customers’ carts when they arrive at checkout. Giving customers a smooth experience is paramount, as crashes directly impact revenue. Medium Stability : Good with the potential to be great Middle of the Pack B2B SaaS, Technology, Finance & Banking, Education, and Telecom all had high stability scores but weren’t quite high enough to meet the standards set by our Trendsetters. B2B SaaS, Technology, Telecom, and Finance & Banking displayed high scores for the second year in a row. Each these industries are involved in significant financial transactions and often are highly regulated. A stable user experience is essential to success, especially when stability translates to higher loyalty and revenue. B2C SaaS/Consumer Mobile, Social, Consumer Goods, Travel & Hospitality all have a strong consumer focus. Consumer Goods, Travel & Hospitality and B2C SaaS have financial transactions that must be secure for consumers’ piece of mind and their continued app use. Low Stability : Nothing special and easily replaceable Run of the Mill Gaming, as in previous editions of our index, continues to lag behind other industries in stability. Despite millions of users, especially among mobile games, these users are less loyal and have no qualms about replacing games with others due to next to none switching costs. To retain these users, games often introduce new features, but this increases  the likelihood of bugs. This explains why Gaming also had the most score variability out of all the included industries. Health & Wellness also scored below the industry-wide mean of our index while demonstrating large variability in scores. These apps still have a way to go to achieve a healthy stability score and should focus on fixing bugs before introducing any new features or capabilities. Web vs Mobile: A Comparison Mobile apps continue to become more stable while web applications show dramatic improvement. In our reports from 2020 and 2021, median mobile app stability score in-creased from 99.63% to 99.80%. This year, median stability score for mobile apps continued to trend upwards, increasing to 99.88% in 2022. While mobile apps are becoming more stable, there is still work to be done to achieve the “five nines” of stability. Web-based applications showed surprising gains in their median stability score. Just two years ago web applications had a median stability score of 99.39%. In 2020 we mentioned this may be due to monitoring and ad-dressing client-side issues in JavaScript applications usually requires more effort than mobile apps. Evidently, there has been significant strides made in adapting this older discipline to today’s needs, as web apps scored a median stability of 99.94% in 2022’s report. While this is excellent news and shows the success of implementing error handling strategies, there is still room to grow to achieve the “five nines,” like mobile apps. Different platforms have different errors Our web applications data includes several front-end development platforms, including Ember, JavaScript, React, and Vue. Each of these platforms is a modern, opinionated JavaScript framework built with consideration for error handling. Some specific causes of unhandled exceptions in web applications may be an event handler bug causing the user interaction to fail, an unhandled promise rejection warning, a bug preventing a page from rendering, and more.  Mobile applications data includes several mobile development platforms, among them Android, iOS, React Native, and Unity. For these applications, stability scores are negatively impacted by session-ending events. This means things like crashes and ANRs (Application Not Responding) in Android, React Native, and Unity frameworks as well as OOMs (Out of Memory) in iOS applications. 30 DAY STABILITY SCORE BY PLATFORM Mobile Platforms Built with Specific Personas in Mind continue to have high median stability scores. One reason for this consistency is the amount of developers specialized in Android and iOS. Their well of knowledge not only helps them fix errors, it helps them do so efficiently. Android and iOS While their median stability scores are similar, the range of scores between Android and iOS applications is noticeably different. Many Android applications have a stability lower than the platform median while iOS applications have a much narrower range. One reason for this discrepancy is because has a much larger number of devices – a more open development environment. This can make it difficult to test applications and increases exposure to crashes and errors. Whereas dedicated development teams have a limited number of devices to test their application’s stability on. Android iOS is a very popular mobile development framework thanks to its ability to simultaneously develop Android and iOS applications. It is especially helpful for engineers that may not be familiar with mobile frameworks but have experience with React for web applications. React Native is extremely popular in the mobile gaming industry, with many of the most popular games developed on the platform. As primarily a mobile gaming framework, it’s not surprising Unity showed the same trends out of the platforms included in our report. Mobile games often introduce new features rapidly to satisfy their users, which can lead to more errors and instability. Feature flags and experiments to introduce new features to a subsegment of users will help improve app stability while minimizing the amount of bugs (or risk) introduced to your application’s entire user base. As an aside, we recently launched support for Unreal Engine earlier this year, however we were unable to use the data for this year’s report. We expect to see Unreal Engine as a platform listed next year. Unity The Versatility Behind Modern Web Application Frameworks and showed similar stability, with JavaScript applications just edging out React applications for the highest stability score. React did have a narrower stability score distribution than JavaScript, which may be a result of JavaScript having a wider range of industries using its framework than React. JavaScript React Each web-based application has its stability measured across multiple browsers. All customers experiencing errors in Google Chrome, Mozilla Firefox, Safari, or other browsers are included in the overall stability score of the application. Sometimes errors may be caused by specific browser extensions, which are included in our stability score. However, most engineering organizations do not dedicate time and resources to fix these bugs because they are not from their application’s code.
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‍As a disclaimer, because the volume of Ember and Vue projects was significantly less than JavaScript and React projects, for the purpose of our analysis we grouped Ember and Vue projects with JavaScript projects. Mobile Apps Release at Almost Twice the Frequency of Web Apps Web and mobile applications are shifting their release cadences as consumers frequently demand new features and immediate bug resolution. We sifted through our data to analyze the release frequency of the leading applications so you can benchmark them against your release cadence. One notable example is the trend of faster releases for mobile apps which update weekly. On average, across all industries mobile apps deliver every four to five days. Meanwhile, web applications adhere to the biweekly release frequency, about every ten days. One possible explanation for the discrepancy is mobile apps more frequently test new features by practicing progressive delivery with feature flags, experiments, and A/B tests to retain their users. This is especially true in mobile gaming apps. Release Cadences Depend on Industry Type Gaming has the narrowest distribution, averaging about 6.5 releases a month. This is an increase over the weekly frequency we saw in last year’s report. The frequent release schedule may help explain why gaming saw the lowest stability score in our report. Health & Wellness had the widest range of distribution as well as the second highest release median. Their second-lowest stability median is proof why there needs to be a balance between frequent and infrequent updates, and how measures like target and critical stability scores can help find that balance. All industries besides Media & Entertainment released a new version of their application on a weekly basis at minimum. It’s becoming clearer developers are more confident in their releases schedules and accelerating new releases through progressive delivery practices like feature flags. Outside of a few industries, each industry displayed a wide range of release schedules, with some releasing multiple times a day. This may indicate bugs are releasing at large scale and teams need to focus on minimizing risk with new features. Key Takeaways Increase stability to grow customer engagement, adoption, and retain loyal customers. App stability is closely tied to overall customer experience and business outcomes. It is no secret happier users become loyal customers. Delivering a dependable, stable application will set your app apart from its competitors. Know when to fix vs build to accelerate release production. The most successful apps closely monitor their app’s stability to determine when to allocate resources to bug fixing for a better user experience or focus on building new features. Freeing up these resources allow for proper allocation to speed up release production while creating exciting new ways to solve customer problems. Grow revenue and market share by delivering desired features faster. Release frequency in web and mobile apps is increasing each year as users want more features faster. Balance roadmap agility with app stability to release new features that are bug-free and grow your app’s competitive advantage. Also published . here

Using Stability as a Barometer of Quality and Quantity

The Ultimate Playbook for Getting More GitHub Stars

Technology is making history more often than the healthcare industry. But if you consider that healthcare is saving human lives, they are equal. The greatest solution for humankind is when they work together to provide a better quality of life, making doctors’ lives easier or routine paperwork less boring. That sounds far too good, so let’s get to the practical side of it. Healthcare applications are becoming more popular with . That’s only mobile applications! To build the mHealth app, we need to choose the right tech stack. The following questions come up: 350 000 mHealth apps available in major app stores How do we set up medical features with backend technologies? How do top healthcare companies use AI in their work? What are successful tech stack examples in the industry? How to set up healthcare cybersecurity? We are simple software developers, so we are interested in technologies for health tech. It’s an interesting observation that health stacks are not entirely different from other industries' tech stacks. There are for sure more requirements for healthcare applications but the same languages, frameworks, and cloud technologies are used to build them. Let’s try to answer the questions we asked above and give tech stack examples. What Is Health Stack? Health stack is the backend and frontend technologies that healthcare companies use to manage their operations. So, except for clinical tasks, healthcare apps can do everything else. Non-clinical tasks include electronic health or medical records (EHR) systems, patient portals, telemedicine platforms, practice management software, billing and claims processing systems, analytics tools, etc. Health stack solutions have to help healthcare organizations improve their processes and improve patient care. But to choose the right tech stack for any app, we need to consider the following factors: Features and functionality of the product (in our case, medical features such as patient and doctor authorization, medical records database, etc.) Project requirements (user quantity, device support, performance time, etc.) The credibility of technologies’ open-source community Simple scalability Security considerations (in medical apps, also HIPAA compliance) Flexibility and the possibility to go beyond standard ways Size and type of your project. Every healthcare solution is unique, although the requirements for most apps will be similar. The reason is that a lot of technologies are added to the development process. Modern Healthcare Tech Stack Components It’s not a complete set of components a health app would need but those that are commonly used by digital health companies and healthcare providers. Java, Python, C#, C++, JavaScript, PHP, and HTML5. Programming Languages: The choice of specific language would depend on the functionality you need. If the app would store and analyze large amounts of data or somehow deal with artificial intelligence, it’s wise to choose Python + Java as backend technologies and Javascript as frontend technologies. Windows, macOS, Linux, and mobile Apple iOS or Google Android. Operating Systems: Here we just need to choose a trustable provider with great support. In the development process, we choose the operating system that has security features and top performance. MySQL, Oracle, PostgreSQL, Memcached, and MongoDB. Databases: To choose the right database or mix a few, seek advice from a development team. They would want to know what type of data you have, the amounts, and how often it’ll be requested. Based on that, they’ll advise the capacity of the database and the provider. Apache server and NGINX. Servers: These two are the most popular ones, but what’s important for us is that they’re HIPAA compliant. Other : tools that often come in handy in the healthcare industry GitHub, Jenkins, Selenium, Rollbar, or Bitbucket DevOps tools: such as Slack, and G Suite - for communication and management Business tools such as Google Analytics, Stripe, or Elasticsearch - for search, analytics, and payments Utilities such as Amazon S3, Amazon EC2, or DigitalOcean Cloud storage and hosting providers Now that we have the general picture of the technology stack that might be used in healthcare apps, here are practical use cases. Tech Stack Examples To be more precise, let’s see the technology stack of some apps developed at Incora. The 1st example is the service we provided to the doctor’s appointment app. used frontend technologies such as JavaScript, TypeScript, React, Antdesign, Java for the backend, and database PostgreSQL. HealthApp, with such a tech stack, allows you to make an appointment online as well as get a consultation from a doctor, nurse, or psychologist online. HealthApp The second example is different as it involved backend technologies. For an where we set the backend and created structure and functionality, we used runtime environment Node.js, also Nest Js for backend, React.js for frontend, AWS services (AWS Lambda), and database PostgreSQL. injury management system With the help of these technologies, Incora developed the management system that provides scheduling of appointments, management of “play status” of players, statistics and reports of all injured players, and emails for different events. Last but not least, the development team set up a backend for It allows the viewing of data about insulin injections, sugar levels, etc., for patients that use specific devices that do injections. patient administration service. The service was designed for doctors to manage patients and adjust treatment. The health stack included Node.js, Express.js, MySQL, React, Redux, Saga, and AWS. Medical Standards in Different Regions This paragraph is to remind you that most industries have . No matter what app you want to develop, make sure the data there (especially patients’ data) is treated the right way. standards and policies when it comes to data protection One of the most common healthcare cybersecurity issues is personal data leakage. Here are : 4 main regulations you need to meet Health Insurance Portability and Accountability Act (HIPAA) (USA). Any mobile health app that needs to comply with HIPAA. Only personal health apps are an exception. deals with protected health information (PHI) Personal Information Protection and Electronic Documents Act (PIPEDA) (Canada). The act sets rules to regulate any personal data usage and sharing with third parties. General Data Protection Regulation (GDPR) (EU). This regulation says ; any information that might identify a person, a name, email, an IP address, and so on. how businesses can and cannot use personal data Data Protection Act (DPA) (UK). It’s similar to GDPR in terms of rules on using and storing personal data. The technologies that we mentioned in the article are well-known and meet the above regulations. However, be sure to check it as the consequences are unpleasant, to say the least. Sum Up So, let’s rewind. We've defined what a health stack is, and what factors to consider when choosing one. Also, we made a list of commonly used technology stacks and tools in the healthcare industry. Furthermore, the tech stack examples were described to have a full picture of app functionality. And finally, we were reminded about healthcare app development standards that are a must nowadays. To save the world, save yourself from bureaucracy, and write us to handle both tech stack and standards.

What Tech Stack do Healthcare Companies Use?

Big Data's value, popularity, and scale of usage in business today come from a few of the indisputable benefits it has to offer: The data is coming from various resources that contribute to its accuracy; The constant influx of data guarantees its relevance; Instead of manual analysis, it is processed automatically with the help of algorithms, which reduce the error probability and allows increasing the data volume; Centralized data access has become possible with the help of Big Data technologies. The world statistics show that since 2015. the number of companies using Big Data has grown from 17% to 50% The increase rate is impressive, and the truth is, it’s no longer just a fancy word a cool tech guy would use when discussing what’s behind supercomputer VIKI from . I, Robot In fact, many large industries have already adopted Big Data technologies and are gaining profit. In this article, I'll look at three industries in which big data is making a dent in 2020. Big Data in Medicine and Healthcare When discussing Big Data in healthcare, one should distinguish the three aspects of its application. Firstly, it’s the so-called . clinical aspect that involves disease diagnosis, treatment, and prevention Then comes aimed at better management of healthcare institutions by improving their operational and economic efficiency, on both regional and governmental levels. the management aspect Finally, is the one where Big Data can play a truly revolutionary role. Disease studies and drug development are the core areas here. the scientific aspect How exactly can Big Data technologies be useful to a particular patient and a specific doctor? The fundamental concept lies within the development of electronic health records (EHR). is a system that related to an individual’s health. EHR contains the , all the hospitalization records and doctor visits, laboratory tests, vaccinations, examinations, allergies, or any other related facts. Apart from serving as a storage of accurate medical data, EHR can control the patient undergo regular screenings and treatments by sending corresponding reminders and notifications. EHR collects and stores medical and other personal data patient’s disease and ailments’ history Many experts claim Blockchain to be a good technology choice for EHR: it fulfills some of its major requirements, such as completeness of data, its protection, and verification. makes it possible to use millions of EHR’s for as social, territorial, age-related, demographic, genomic, etc., which in its turn, allows providing a patient with exceptionally individual recommendations. The synergy of these three rising technologies allows creating a diagnostic system of a brand new quality level. Combining Blockchain with Big Data and AI detecting hidden dependencies between a disease along with other side-factors is a prototype example of such a system. Its database as well as 2 000 000 text pages from medical journals and clinic tests. By processing this data, the program . Watson for Oncology by IBM includes more than 600 000 diagnosis records can produce the most optimal treatment plan A retrospective analysis of treatment plans prescribed says that in regards to lung cancer, . In comparison, the rate of around . Watson selected efficient treatment tactics in 90% of the cases US hospitals averaged 50% Big Data also represents the core technology for forecasting medical institutions’ spending. It relies on a multifactor analysis of such statistical data as the number of repeat visits, ailments recorded against specific experts and departments, the prevalence of certain pathologies, number of chronic patients, epidemiologic indicators, etc. serves as a good example here: they . Repeated hospitalization, missed doctor appointments, drug supply are the major factors included. British National Health Service use Big Data to analyze the efficiency of surgery sub-departments McKinsey’s recent research says that . McKinsey reports that it can be achieved through Big Data capability to unite the data stored in separate sources wholly isolated from one another. For instance: Big Data helps to not only reduce healthcare costs but also contributes to the quality of life enhancement Consolidating these types of data from the sources above opens up unique possibilities for the medicare. Clinic data (medical history, laboratory tests, etc.); Patients’ behavior insights based on purchase preferences - the data collected from portable and home medical devices; Scientific research and tests; Medical establishments’ records of the services provided: pharmacies’ reports on the drugs sold, price statistics from the healthcare market. Optimizing the operational activities is essential for bringing the established treatment practices to a whole new level. Personalized and preventive approaches based on remote monitoring can become the new reality thanks to vast volumes being analyzed. Big Data in Retail Every minute millions of people are purchasing by carrying out millions of transactions, so it’s no surprise that retail is one of the top industries leveraging Big Data. The significant tasks retail is trying to solve from both are the following: technological and entrepreneur standpoints Any retail business is looking for very explicit recommendations which steps one should take in a particular situation. Nowadays, Big Data analytics can help with that. One of the aspects of a company’s steady income depends on — is the . Price correction is one of the principal retail management mechanisms. The studies show that, on average, managers spend half of their work time on goods reevaluation, which still isn’t accurate enough due to human factors. In addition, one cannot guarantee that the process operates such crucial variables as seasonality, stock availability, supply and demand structure, competitors’ activities, etc. That is why large . smart pricing policy retail chains switch to automatized price reevaluation using Big Data technologies Process huge amounts of data;Get updates on the sales performed and the stock dynamics in the entire retail chain; React quickly to the changing situations and produce forecasts by addressing all the contributing factors (weather conditions, seasonality, holidays, distribution points, competitors, etc.); Analyze promo activities. , has implemented a similar solution, which has . What’s also important here, the new price wasn’t just somebody’s judgment call but was carefully deduced, relying on the variables mentioned above. Macy’s, which operates 800 stores with 73 trade items spared the need for pricing correction by 22 times Using the same method, . Amazon is adjusting its prices every two minutes Apart from the optimizations the technology brings to the existing businesses, it plays a big role in making strategic decisions when developing a new entity. By analyzing competitors’ locations nearby, transport access, potential customers’ income rate, their habits, and preferences, it gives a comprehensive idea of the territory’s commercial potential for future business. Big Data in Law Enforcement Historically, law-enforcement facilities have been working with huge volumes of data. There are few directions where data-based insights can be of particular value to the law-enforcement establishments. First and foremost, it’s cybersecurity. As unfortunate as it may seem, but fraudulent activities and malware have become a very often type of crime for today’s police. is said to be . Big Data algorithms can detect suspicious activities before they actually occur and alert consumers or companies about a potentially fraudulent action. It’s becoming a must for many businesses to take proper care of enterprise data security. Big Data analytical function today’s most efficient instrument for fraud identification and prevention Big Data analytics is also behind modern policing strategies. It allows the police to take a more proactive role in combating criminal activities. By using various sources of data such as the number of arrests, crime rates, fines issued in regards to a particular neighborhood, the police can monitor the areas prone to criminal activities more closely. Predictive policing — is the term used to describe this method in criminology. Lastly, on various levels. It gives the authorities unprecedented access to very different kinds of precise information from all over the world to help understand the global picture of a situation and make well-informed decisions. Economy, health, climate, social issues are just a few fields the law enforcement agencies need data science analytics for. advanced analytics Big Data offers is an efficient tool for governing establishments Summary “Information is the oil of the 21st century, and analytics is the combustion engine” — Peter Sondergaard at Gartner. It’s safe to say that data truly is the new oil, today. But a great opportunity can be a big challenge at the same time. So if you are having a hard time with structuring and organizing your business data and you feel like there is a better way to deal with it, reach out to me!

3 Industries Harnessing the Power of Big Data: Healthcare, Law, and Retail

The idea of an AI-driven robot taking over our healthcare – one of the most “human” fields that we have – is not a new one. Until recently, however, the idea remained relatively firmly in the realm of science fiction books and movies. But with the viral success of ChatGPT, the discussion of what this new generation of AI will be doing for us in the future has started to come up in the healthcare field. Now we’re not saying that you’ll be talking to a robot doctor at your next annual checkup any time soon, but we have to ask the question… Could ChatGPT be your doctor in the future? How Does ChatGPT Work? Without getting too deep into AI and Machine Learning, let’s define ChatGPT. The initials “GPT” stand for “Generative Pre-training Transformer,” three fundamental properties of the world’s most famous (currently) Artificial Intelligence that already provide a description of how it works: : More specifically than an AI, ChatGPT is a generative language model, a program that has been trained to hold natural conversations with humans. Generative : ChatGPT was pre-trained using the largest text dataset ever used for this purpose. Furthermore, the company behind ChatGPT, OpenAI, also trained its product through human feedback. Pre-Training : ChatGPT is built on transformers, which are a type of artificial neural network architecture that allows it to elaborate an input with the information it has been trained with and produce an output. Transformer How is ChatGPT Similar to Doctors? Simply put, ChatGPT must be trained with datasets in order to process inputs and generate answers that are understandable and accurate to humans. Sounds familiar? This process is similar to the path our society has outlined for anyone seeking to become a professional – in our case, a medical doctor. Doctors are among the professions that require the most years of university education, studying from books and through lessons (datasets) before they can finally talk to patients (receive inputs), provide their diagnosis, and recommend specific treatments (generate outputs). Only in its infancy, ChatGPT is already a remarkable product, but it is still far from being sufficiently advanced to trust with healthcare decisions or diagnoses. AIs require training on specialized data sets in order to perform specialized functions, and ChatGPT just isn’t trained for healthcare purposes. In fact, when we asked ChatGPT if it could provide medical diagnoses, it responded: “ .” No, I’m sorry, but as an AI language model, I am not qualified to make medical diagnoses. My programming and training are focused on understanding and processing natural language to provide information, answer questions, and assist with a wide range of tasks. However, I can provide you with general information on medical conditions and their symptoms, as well as advice on seeking professional medical help. If you have a specific medical concern, it’s always best to consult with a licensed medical professional who can properly diagnose and treat your condition For now, doctors all over the world can breathe easily. However, if a new version of ChatGPT was developed – one fed with a dataset of scientific information about healthcare and medicine that is thousands of times larger than any amount of material humans can effectively learn – it could mean a drastic and possibly rapid shift in how we receive our healthcare. If functionality included voice recognition and medical imaging machine learning, such a tool could not only perform initial patient assessments and triage but could potentially become a primary tool - or at least a supplementary tool - for diagnosis in hospitals and clinics. Human doctors will always have their advantages. Being people, they always have the capacity for empathy and provide the crucial human, emotional and psychological support that patients need to recuperate. Humans are also better at innovative ideas and improvisation, both of which are crucial in ERs, operating theaters, and many other areas of healthcare. But AI models like ChatGPT may soon be able to provide critical support to their work and may even be a potential solution to over-stressed healthcare networks and national services. The Shift to AI May Not be Seamless Nevertheless, the implementation of AI in our daily lives may not be as smooth as one might expect. For example, in order to have a trustworthy product, AIs must be trained with reliable medical data. Furthermore, several paradoxes may emerge from a new collaboration between humans and robots. For example, the AI may use its sophisticated algorithms and data analysis to come up with a diagnosis, whereas the medical doctor may rely on their professional experience and intuition to make a different diagnosis. Which diagnosis should take precedence if the doctor and the AI arrive at opposing conclusions? What happens if a doctor and AI team disagree with the diagnosis of another doctor and AI team? Even without a deep dive into the ethics and implementation, it is obvious that - before any AI integration occurs - experts and governments must discuss a robust framework to regulate scenarios like this one. For these and other reasons, such a change may appear radical or even dangerous to many, but when one zooms out and considers the incredible advancements in medicine over the last century, as well as the incredibly fast rate at which things continue to change today, we think it’s safe to assume that future generations will have AI robots like ChatGPT covering some diagnoses and taking care of their health on a daily basis. In less than 100 years, we’ve gone from the discovery of penicillin to custom-printed drugs created through genetics-powered personalized healthcare. In the last few decades alone, we’ve doubled cancer survival rates for almost every type of cancer. Nearly every discipline of our healthcare is seeing benefits from technology, as well as a shift towards data-driven, patient-centric medicine. AI will play a major part in the fourth industrial revolution, and both medical practice and research are already beginning to be more and more driven by these advancements. Multnomah County Hospital, 1948 ( ) vs. Modern Medical Facility ( ) Source Source Conclusion History repeats itself: as it happened with the introduction of computers and of the internet, AI and similar other disruptive technologies are inevitably going to cause rapid and profound changes in every aspect of our society. AI technology is already being used in many healthcare sectors to diagnose and treat illnesses, automate medical processes, to discover and print new drugs, and further advancements are likely to have a major impact on the way medical care is provided. is an EU-funded startup aiming to solve the issues of access to and bias in data in order to ensure these technological developments are equitable and trustworthy, and board chair Dr. Ligia Kornowska is also the leader of the “AI in Healthcare” Coalition. She was instrumental in the creation of the , discussing the benefits, concerns, and ethical guidelines required when it comes to the use of AI in healthcare. It will take many similar efforts from governmental institutions and citizen organizations to ensure AI is properly and ethically implemented, with sufficient oversight and a patient-centric focus. Data Lake “AI in Clinical Practice” whitepaper This is an exciting time for healthcare, and as we move towards a digitalized future, it is our duty as a society to prepare for the impact of these technologies and begin a discussion on how they can be useful for humankind in a safe manner. Could ChatGPT replace your doctor? Well, it’s certainly not going to happen today or any time soon. However, as the introduction of computers and the internet brought profound changes to the way we live, work, and interact, the introduction of AI is certain to have a similarly dramatic impact on medicine and healthcare. This article was written by the staff of Data Lake, an EU-funded startup working to provide ethical access to medical data for pro-patient research and development purposes. Also published . here

ChatGPT Could Have a Profound Impact on the Healthcare of the Future

How to Prevent Apple From Reading Your Messages If you are an iPhone user, and your friends, too, probably use the Apple iMessage app for day-to-day communication. Apart from the app being intuitive and convenient, it also provides to safeguard your conversations. The encryption, by default, can protect your messages from Apple’s eyes, too. end-to-end encryption Last month, there was a report detailing the Problem in the end-to-end encryption of Whatsapp. This time, I would like to take a closer look at another popular messaging platform — Apple iMessage. In General, Apple Cannot Read Your Messages. The iMessage, by design, uses end-to-end encryption in a way that messages from the sender’s Apple device to another Apple device are only viewable by them. Each party contains a unique “key” to open the “envelope” containing the message. As such, without the key, if someone theoretically intercepts the conversation, the message is protected. Fundamentally, this end-to-end encryption works as expected. Only your connected devices and the Apple devices that receive your messages have the keys to unlock and read those messages. Law enforcement or any other third party cannot read your messages without access to your unlocked device, nor Apple can. *Note that only iMessages are encrypted; SMS texts are not encrypted (the other hand shows up as green bubbles in Messages instead of the standard blue). There’s One Problem — iCloud Although messages are encrypted, When we talked about data encryption, we considered three stages of data: it is not always encrypted. Data-in-use Data-in-transit Data-at-rest In this case, iMessage protects your message in data-in-motion primarily. However, if you are like everyone — keeping the messages around in case we want to read them later; few of us delete all texts immediately once they come in — which means the messages stored on the device (data-at-rest) and might need to back up somehow. Here comes the problem, you back up your messages might decide between having a genuinely secure iMessage history and how giving Apple the key to unlock all your conversations. Using iCloud vs. iCloud Backup First of all, let’s talk about . As the name suggests, it backs up your messages to your account and sync across your connected Apple devices. So it’s handy to start a chat on your iPhone and then continue it on your Mac or iPad and doubles as a reliable backup method (messages are stored locally among devices). Messages in iCloud Second, the is for backing up the contents of your iPhone. Besides, an iCloud Backup can store many things, from app data to device settings, configurations, photos and videos, and obviously, messages. So the two aren’t mutually exclusive; you can use both at once. And when you do, though, iCloud Backup Apple keeps your message history separately from your device’s iCloud Backup. iCloud Focuses on Availability, Not Confidentiality As mentioned, — that’s why there’s no way to access your texts on the web (as described above in end-to-end encryption, data-in-use), such as by logging in to . However, there’s one big problem: messages kept in iCloud are end-to-end encrypted icloud.com your iCloud Backup isn’t end-to-end encrypted, i.e., for data-at-rest. Apple does this to provide a “backup” to your Backup. Because Apple doesn’t want you to lose your data forever, imagine that you forget your Apple ID password or your device’s unlock passcode, which means you lost access or lost the key stored on the device. As a result, That’s what would happen if iCloud backups, and the data inside, were end-to-end encrypted. the Backup would be inaccessible forever. To avoid this from happening, iCloud Data Recovery Service can retrieve any data backed up to iCloud that is not encrypted (most of your data). Many people are likely relieved when Apple “saves” their messages in this situation. But for those who are privacy-conscious, sadly, they are likely unsettled. Apple stores the key to opening your encrypted messages within that Backup. In addition, apple’s Apart from messages, information like Keychain, Screen Time, and Health data are included in the iCloud Backup that Apple has the key to decrypt. Fortunately, I cannot find any news or report claiming Apple has ever decrypted users’ messages and data using the keys they have stored in iCloud. But that’s not the problem. Instead, the problem is the possibility that Apple could do so if they wanted to, or, even worse, when they were forced to share the key with law enforcement by order. I want to extend the seriousness of the problem here: if there was a data breach within the iCloud, hackers could acquire the key and thus your data. Because, as you already know, the key is stored with the safe itself. How to Prevent Apple From Peeping Your Messages That’s is pretty straightforward: . That said, you lose the convenience of recovery on any device (or, oppositely, you gave up your privacy when choosing over comfort). On the other hand, your privacy is preserved without storing your end-to-end encryption key and the rest of your messages in plaintext. Don’t use iCloud Backup to store old texts Of course, that doesn’t mean you can’t back up your messages. Messages in iCloud are still end-to-end encrypted, which implies that even though you’re saving those messages in the cloud, Apple doesn’t have the key to decrypt them. If you are using iCloud Backup, you can turn it off by: . Settings > Apple ID > iCloud > iCloud Backup Ensure the toggle next to is gray. iCloud Backup When you disable iCloud Backup, your last Backup will remain in the cloud for 180 days. That means is that once iCloud Backup is disabled, a new key is generated for future messages; from here on out, your new messages are protected. you need to wait half a year until you can be assured Apple no longer has the key to your messages on its servers. However, the good news Alternative Backup Method If you want to use the secure Messages in iCloud feature to Backup and sync your conversations, you can check its status from the iCloud settings page: the toggle next to should be green. Messages If you want an alternative backup solution, you can: Use your iPhone to your computer via Finder (macOS Catalina or later) or iTunes (Windows or macOS Mojave or earlier). Apple has an easy-to-follow for data backup locally. guide If you want to enhance the availability of your Backup (in case the local copies are corrupted or lost), before you upload it to the iCloud or other storage services, But remember, (no matter it is a password, certificate, or token). you can encrypt those backups. please keep the encryption key safe and secure Final Words — You’re Never Fully Protected Using iMessage You can take the steps above to make sure that the messages on your side are end-to-end encrypted. But you need to know that most of us do not talk to ourselves using the messaging platform; we speak to someone else. Thus, there’s no way to know if the person you are texting has iCloud Backup enabled. And if they do, that would give Apple the encryption key to all the messages you sent that person. You can’t control the actions of everyone you text. Moreover, even if you know the messages never leave the devices of the people involved in the conversation, or even better, you use messaging apps like Signal to send self-deleted messages; nothing stops other people from taking photos of your discussions or handing their device over to another party. This is what we are facing — . But we should try our best with the data on our reach to control and encourage those around us to employ privacy practices and cyber hygiene. the problem of trust versus the control of our privacy Thank you for reading. May InfoSec is with you🖖.

You're Never Fully Protected Using iMessage

image source: unsplash.com In today’s digital age, whether we know it or not, we very much depend on data as many decisions which directly impact us are made using it, from what medicine will be included in our our health insurance plan,to how much our house will cost and everything in between. Recently, thanks to the growth of technologies such as IoT, AI and Machine Learning, the systems data scientists use to collect, analyze and disseminate data have undergone major disruptions. With the technological revolution, the data market has seen with the big data industry‘s estimated worth currently holding at $42 billion with forecasts predicting it to hit $103 billion by 2027. The International Data Corporation (IDC) that the amount of data in the world will reach 163 trillion gigabytes by 2025. explosive growth estimates However, the industry is still experiencing issues stopping it from reaching its full potential, which, when solved will lead to further growth in the space. The Problem With the Data Science Industry Most profit and non-profit organizations lack the know-how and resources necessary to fully take advantage of the scientific data they generate and the majority of these firms do not utilize data generated by other organizations because they do not know how to access and make use of it. According to a , only 4% of firms can extract the full value of the information they possess. survey by PwC and Iron Mountain attribute the low uptake to several factors such as high data integration costs, lack of infrastructure, time required to collect and analyze data, and concerns over data quality among other issues.. Researchers The chart below shows the top problems preventing firms from turning their data into usable insights. Source: Big Data Made Simple It is important to note that these challenges apply to both the scientific and non-scientific research. The Blockchain Solution Blockchain offers a decentralized and highly transparent platform where individual researchers, non-profits, and for-profit organizations can trade scientific data. Firstly, the transparency blockchain offers ensures that only reputable sources can share data and everyone can track the process through which the data is acquired and presented. Secondly, the elimination of intermediaries means reduced costs for data buyers and maximized profits for data sellers. Traditionally, data owners have to depend on intermediaries to sell their data in centralized data marketplaces which are not only costly but are also vague about what the data will be used for. Thirdly, the availability of a single, decentralized platform where researchers can trade data eliminates geographical and regulatory barriers associated with the conventional methods of sharing data. A blockchain project known as is an excellent example for a decentralized solution to scientific data storage and sharing. The SciDex project takes advantage of blockchain, AI, Machine Learning and Natural Language processing to provide a platform where data providers and researchers can trade data. SciDex So if, for example a manufacturer of prescription drugs wants to release a new drug for Asthma patients, they need to conduct a study to determine the effectiveness of the drug. For the study to be accurate, the company must consider many variables such as the change of weather and air pollution in the target area. Instead of carrying out the studies about these variables themselves and spending huge sums on research and staff, the company can source the data from the SciDex search engine. There, they simply search for and connect with the listed providers who have similar data. If there is no relevant data for the target area, the company can make a call for contribution on the platform and data scientists in those areas will respond. The platform utilizes Ricardian Adaptive smart contracts to match data needs and offerings and a cryptocurrency known as SciToken to facilitate transactions. The SciToken can be reused on the platform or converted into other cryptos or fiat money. For small and medium entities without IT or legal capabilities, SciDex is working on tools to integrate them with its dashboard and Index. Also, a tool will be available to help them connect with , a blockchain-ready community for intellectual property licensing. COALA IP The same case applies for university researchers with interest in individual or corporate data. The researchers will have an opportunity to help organizations outside the academic arena by providing their services for data collection and curation. Even though the SciDex solution is not the only project enabling incentivized data sharing on the blockchain, it is the first to combine scientific research and blockchain. With the rate at which big data and cutting edge technologies in AI, Machine Learning and blockchain are growing, there is high hope that better things are yet to come which will change data science, making it cheaper, more accessible and more accurate leading to better decision making and more accurate results for companies and consumers alike.

Blockchain is Changing the Data Landscape For the Better

Thriving mobile app technology has made our daily activities easier. Hundreds of thousands of mobile apps are available in the app store in the ‘health and fitness’ category to make our life more comfortable and healthier. This surge in the number of fitness apps is largely attributed to the fitness boom that occurred in the year 2014 with the advent of wearables. However, the trend quickly shifted in favor of the mobile apps because they can effectively control the wearables as well. Today, as the number of smartphone users increases by leaps and bound, the popularity of customized fitness apps is increasing continually. Statista has predicted that globally, the will surpass the figure of 353 million by 2022. has estimated that the mHealth apps revenue will expand to $31 billion by 2020. Taking cognizance of this scenario, both Google and Apple have come up with Google Fit and Health Kit respectively to facilitate mobile app development for the Health and Fitness domain. number of fitness app users Another report Types of Health and Fitness Apps It is indeed quite a task for the fitness companies to stand ahead of the curve with a tailored mobile app. It is necessary to keep the in mind along with the current direction of the niche market and the user behavior while developing a health and fitness app. \ health and fitness trends These days, four types of health and fitness apps are in vogue to improve the user’s health and lifestyle: Such apps track all the physical activities like walking, cycling, running, and jogging. These apps use the motion sensors of smartphones to provide the accurate data of the individual’s activities. Activity Tracking- As the name suggests, such apps can act as a gym instructor. A personal trainer app is more useful for people who cannot spare time to visit the gym due to a hectic work schedule. Personal Trainer- Health-conscious people love this type of app as it takes care of the calorie and nutritional value of daily food. It shows the nutrition chart and helps users take a balanced diet. Diet and Nutrition- The holistic approach of health includes both physical and psychological wellness. Yoga and meditation can keep the body and mind in the fine shape and keep you relaxed. Yoga and Meditation- A high-end integrates the features of two or more categories to give end-to-end fitness solutions. However, new players should stick to any one category for ensuring better penetration in the fitness app domain. Also, feature integration is proportional to the development duration and the cost of an app, and therefore, it is advisable to start with minimum necessary features. health and fitness app Most Sought After Features of Health and Fitness Apps Here we describe a few noteworthy features to be included in the tailored health and fitness mobile app to attract and retain more people: Easy Sign-up Users hate a lengthy and complex registration process. You need to enable the first-time users to create their account with social media accounts. Or, you can make the entire process short and simple by asking for name, email id, and mobile number. The app will send the verification code (OTP) to the given mobile number, and the user gets registered. User Profile The second most important feature is a user profile. Here, the users enter their personal data like age, weight, etc. You can make the profile stronger and inclusive to give your users all types of personal information at a stretch. Also, in future, if you want to add functionalities related to healthcare in your fitness app, the detailed user profile can help you a lot. Social Media Integration From signing up to sharing fitness-related activities, the social media integration can serve many objectives for your app users. You can also get a social media advantage as the users spread a good word on their social accounts for your app. The social media integration can also boost the online search for your application. 2. Wearable Device Connection As the wearable devices have started gaining ground swiftly, it is beneficial for you to connect the app with the wearable devices. It enables the users to monitor or track their fitness activities on the wearables with ease. In a way, the wearable device connectivity also makes your app more user-friendly. 3. Record Tracking Be it a workout plan or diet plan, your app needs to keep the record of the user’s activity and fitness schedule. From individual activities like cycling, walking, etc. to calories burned and weight reduction- the fitness app should track everything and show the real-time situation to the users. You can also add a functionality of planning a meal. 4. Geo location Facility This is one of the most important features for a health and fitness application. The geolocation feature enables your app to monitor direction and routes when the users go for walking, cycling, or jogging. Also, it enables the users to know their exact location. 5. Push Notification Well, push notifications can motivate the app users to achieve their goals. You can encourage the users for regular exercises with inspirational quotes through notifications. Also, the users can set up reminders for the workout, and push notification can effectively remind them on time. 6. Video Tutorials Many people like workouts and exercises, but they have no idea where to start from. Live video tutorials can help them to know the ins and outs of workout. Video tutorials also show the right way to do a particular exercise. It is easy to give necessary tips regarding workout and their impact on a particular part of the body with video tutorials. 7. In-app Purchase You can offer the option of purchasing fitness equipment and health drinks through in-app purchase features. It makes your fitness app complete and the users do not need to visit some other app or website for buying the equipment or a complementary health drink. This feature can save the user’s time and offers you an opportunity to earn some money. 8. Safe and Simple Payment Options You can offer premium features or an ad-free version of your app with a small fee. Also, the in-app purchase feature can also need payment gateway integration. You need to make sure that the payment options are safe and convenient for the users to get the most from app monetization methods. You can also consider offering unique features like loyalty program, reward for workouts, and the like to attract more people toward your app. Along with these features, simple yet attractive UI and a pleasant user experience are also necessary to ensure your app’s success in the app stores. Additional features of the fitness mobile app are a direct chat with the gym instructors and built-in soothing music during the workouts. Such features can make your app more acceptable to a huge audience. Here it is worth to mention that you should prefer a reputed and reliable to get a high-quality fitness app. After discussing the features, let us move to the cost estimation for your health and fitness app. mobile app development company to the freelancers Cost of Health and Fitness Apps Costing of a fitness application largely depends on two factors: feature integration and development duration. Though both these factors are interrelated, they need to be considered as major factors. Another factor is an hourly rate. Let us go through these factors one after another: Complex apps have many features, and integration of many features cost higher than the integration of fewer features. What’s more, the complex app needs an extended team of professionals that comprises a couple of app developers and a salesperson. It increases the app development cost significantly. Feature Integration- The duration of app development largely depends on the number of features you want to include in the app. Also, the development platform is also important in determining the cost. For example, Android app development requires more extensive testing because of a plethora of devices with different screen sizes. 2. Development Duration- There is a great variation in the hourly rate across the world. On one hand, American and Canadian app developers charge above an hour, and on the other hand, Indian app developers take just above an hour. It is better to from a reliable fitness application development company to meet the requirements in a cost-effective way. 3. Hourly Rate- $160 $25 hire mobile app developers Approximately, the fitness app development process takes over 1000 hours depending on the feature integration and other development procedures. For example, the documentation takes up to 40 hours, whereas the designing phase can last up to 70 hours, etc. 4. Summing up all the development aspects, the cost of fitness app remains in a range of . You need to consult the to get the exact estimate depending on your project’s requirements. $25000 to $50000 mobile application development company Also, it is advisable to keep some amount aside for support and maintenance cost to keep your app up-to-date. Conclusion The health and fitness domain thrives as people tend to focus on remaining fit and active. A feature-rich fitness app can leverage you the benefits from this prevalent trend. All you need to contact the reputed app development company and give them your app idea. We offer enterprise-grade . Just connect with us to get 360-degree fitness app solutions. mobile app development services

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