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Diabetes


Artificial Intelligence in Diabetes Management Market Overview with Detailed Analysis, Competitive landscape, Forecast to 2026

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Worldwide Global Artificial Intelligence in Diabetes Management Market report of 2019 provides a detailed market overview as well as industry analysis for / of companies, manufacturers and distributors covering data on gross margin, cost structure, value, sale price and more. It also ensembles the challenges prevalent in this industry vertical and identifies opportunities that will further aid business expansion. Further, the report revisits all areas of the business to cover the impact of COVID-19 pandemic so as to assist stakeholders in devising new strategies and reinforcing their position in the market.


How AI Platforms Are Improving Talent Management In 2020

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Bottom Line: Dexcom and Micron adopting a single AI platform for talent management that adapts to their specific HR strategies and provides new insights is delivering significant results. AI-based platforms provide new insights, intelligence and guidance to CHROs and HR leaders, helping them close the growing talent gaps their organizations face. By integrating hiring, internal mobility, diversity & inclusion, contingent workforces, training & development and performance management all on a single AI platform, HR leaders gain greater insights into closing talent gaps. And it's encouraging to see how AI platforms evaluate candidates on their capabilities while anonymizing factors that might lead to hiring bias. Interested in learning more about why AI platforms are gaining adoption, I recently attended a webinar co-hosted by Talent Tech Lab (TTL) and Eightfold.ai The webinar is titled An AI-First Approach to Recruiting with Eightfold and TTL.


5 Most Computer Vision Algorithms and Applications Instances

#artificialintelligence

Recent developments in computer vision provide tools to the data scientists to automate a broader range of tasks. Yet companies keep wondering how best to recruit machine learning for their particular niche. One of the most common problems is recognizing how a machine learning model will perform the task uniquely than an individual would. Computer vision is an integrative field that enables computers to recognize, process, and analyse images. It uses algorithms that can process both static images and videos.


Artificial intelligence in health care: preparing for the fifth Industrial Revolution

#artificialintelligence

AI has arrived, with the potential for enormous change in the delivery of health care, but are we ready? Artificial intelligence (AI) is the trigger for the next great transformation of society: the fifth Industrial Revolution. AI has already arrived in health care, but are we ready for the kind of changes that it will introduce? In this article, we map out the current areas where AI has begun to permeate and make predictions about the kind of changes it will make to health care. AI comprises any digital system "that mimics human reasoning capabilities, including pattern recognition, abstract reasoning and planning".1 It includes the concept of machine learning, where machines are able to learn from experience in ways that mimic human behaviour, but with the ability to assimilate much more data and with potential for greater accuracy and speed.


The Smart Way To Profit Off The "Internet Of Things"

#artificialintelligence

CHINA - 2020/08/13: In this photo illustration the American multinational technology company and ... [ ] search engine Google logo is seen on an Android mobile device with United States of America flag in the background. Google (GOOG) just made a statement. On August 3, Google announced that it's investing $450 million in home security company ADT (ADT). The investment will give Google a 6.6% stake in the company. You might be wondering why the tech giant wants anything to do with ADT.


One Drop Launches Digital Membership for Whole-Person Approach to Chronic Condition Self-Care

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One Drop, a New York City-based provider of digital health solutions for people living with diabetes and other chronic conditions, today announced the launch of its Digital Membership, a new direct-to-consumer subscription service providing a whole-person approach to chronic condition self-care. With the new Digital Membership, One Drop will expand its proactive, preventative AI-powered solution to support people living with diabetes, prediabetes, high blood pressure, high cholesterol, or any combination of these conditions. Based on each individual's health profile and personal preferences, subscribers to One Drop also receive a customized health transformation plan, including educational resources and interactive elements that improve health literacy, keep people engaged, and encourage positive behavior change. As users work towards customized health goals for A1C, blood pressure, weight, and/or activity, they are encouraged to chat one-on-one with their personal coach, particularly when they are at risk of not meeting their goals or relapsing to a less healthy state. All One Drop coaches are certified health professionals trained in behavioral science techniques such as cognitive behavioral therapy, acceptance and commitment therapy, and motivational interviewing.


Smartphone App And Deep Learning Help Detect Diabetes

#artificialintelligence

Diabetes is one of the world's top causes of disease and death, affecting more than 450 million people worldwide. While technology has come a long way in helping to detect and manage diabetes, it still typically involves blood draws and clinical tools. Moreover, around half of all people with diabetes aren't even aware that they have the disease. Researchers at UC San Francisco have now come up with a promising method of detecting diabetes using a smartphone camera and some deep learning, utilizing the publicly available Instant Heart Rate app from Azumio to capture photoplethysmography (PPG) measurements. When a user places his or her fingertip over the phone's flashlight and camera, the app measures PPG's by capturing color changes in the fingertip corresponding to each heartbeat. This data is reported back to the user as the instantaneous heart rate.


Artificial Intelligence in Outpatient Practice Today

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In the near future, MDs could get new helpful assistants, i.e. efficient multipurpose artificial intelligence (AI) algorithms that will assist them in examining and diagnosing patients, choosing the best treatment strategy, processing patients' requests, and keeping medical records. Currently, there are technologies that support physicians at every stage of treatment. Let's see how AI helps doctors in outpatient practice. One of the promising areas in outpatient practice is the introduction of chatbots. AI will quickly collect and analyze general symptoms of the condition, and then schedule an appointment with the right MD.


Machine-learning test may improve kidney failure prediction in patients with diabetes

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For patients with type 2 diabetes or the APOL1-HR genotype, a machine learning test integrating biomarkers and electronic health record data demonstrated improved prediction of kidney failure compared with commonly used clinical models. According to Kinsuk Chauhan, MD, MPH, of Icahn School of Medicine at Mount Sinai, and colleagues, diabetic kidney disease from type 2 diabetes accounts for 44% of all patients with end-stage kidney disease, with the APOL1 high-risk genotypes also associated with increased risk for chronic kidney disease progression and eGFR decline that may ultimately result in kidney failure. "Even though these populations are on average higher risk than the general population, accurate prediction of who will have rapid kidney function decline (RKFD) and worse kidney outcomes is lacking," the researchers wrote, noting that the current standard of using the kidney failure risk equation to predict ESKD has only been validated in patients who already have kidney disease and not in those with preserved kidney function at baseline. "Widespread electronic health records (EHR) usage provides the potential to leverage thousands of clinical features," the researchers added. "Standard statistical approaches are inadequate to leverage this data due to feature volume, unaligned nature of data and correlation structure."


Coronavirus doctor's diary: How gardening could help in the fight against obesity

BBC News

Being overweight puts you at greater risk of serious illness or death from Covid-19, experts say - and now new anti-obesity strategies have been launched around the UK. In Bradford, community schemes to promote healthy lifestyles offers a novel approach to the problem. Dr John Wright of the city's Royal Infirmary explains why radical thinking is necessary. Our complete concentration on Covid-19 has concealed another global pandemic that has been more insidious but much more harmful: obesity. Early in the pandemic, we spotted common patterns in our sickest Covid-19 patients - they were more likely to have diabetes and heart disease and, in particular, to be obese.