Diabetes


How Digital Is Transforming Child Healthcare - CXOtoday.com

#artificialintelligence

Just imagine a day in your life, where you would no longer have to wait for weeks to visit your paediatrician, followed by an additional wait for your child's health test results and then still more waiting to get an accurate child health record. We are all aware that the constantly altering demographic drifts in child healthcare, the escalating child population and a steeping rise in various chronic illnesses that children these days are suffering from, have nothing but created an enormous demand for health care and social care services for children. Given the superiority of the 21st-century technology, the major question that arises is how can we modify the child health care system to better cope with the rising healthcare needs? The solution to this concern is nothing but efficiently digitalizing child health care to bring in more innovation. Electronic child healthcare is something that needs to be given immediate attention.


Algorithms will out-perform Doctors in just 10 years time - Dataconomy

#artificialintelligence

A recent study done at Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School, showed that AI isn't about Humans versus Machines. A new study is published every month, which proves this potential: even today, such diagnostic algorithms have an error rate of only 5% when detecting melanoma. The surprising insight of those tournaments is that the teams with the strongest human / machine partnership dominate even the strongest computer. Diabetes patients, for example, can already bring their diabetes level to normal levels without any medication, simply by using monitoring tools in conjunction with online coaching from their doctor.


Machine learning: what's the diagnosis?

#artificialintelligence

While doctors try to predict who is at risk based on health and behaviours, humans only have a 30% success rate. Here too, AI can save time and increase accuracy. As well as decreasing the number of false results, the AI software can review 500 charts in a few hours, saving doctors 500 hours of their time. In partnership with Hitachi, Salford Royal Foundation Trust and Salford Clinical Commissioning Group, Salford now has an integrated electronic records system, meaning that people at greatest risk of developing type 2 diabetes can be identified and supported to work towards healthy lifestyle goals.


How AI makes better people

#artificialintelligence

Ming spoke about artificial intelligence (AI) and the future of human potential. Ming shared some of the AI algorithms she has worked on at various start-ups and companies, and how they have helped maximise human potential. So, she built an AI model that now predicts three hours ahead whether her son's blood glucose levels will go high or low. She said often big tech companies hire based on how prestigious the candidate's university was and how high their grades were.


JDRF Partners with IBM to Research Type 1 Diabetes

#artificialintelligence

IBM and JDRF have come together to comprehensively study and analyze several years of voluminous data available for Type 1 diabetes (I1D) among children. IBM scientists will use the artificial intelligence (AI) technology to analyze at least three data sets. As the leading funder of T1D research, JDRF's partnership with IBM will uncover previously unseen data trends. But their previous projects did not analyze data comprehensively.


DXC Labs: Using data stories to accelerate machine learning solutions – DXC Blogs

#artificialintelligence

DXC Labs has been leading the R&D for our industrialized AI offering by rapidly developing prototypes of machine learning solutions for various "data stories." For customers, our prototypes provide visualizations of the predicted results as "actionable insights" in Microsoft's Power BI that can be drilled into for further analysis. The data story was: "Reduce patient care cost and improve patient care and logistics for elective care." Predicting diabetes risk to reduce patient care costs -- visualizations of the actionable insights obtained from otherwise disparate data.


Five lessons banks can learn from disrupted industries

#artificialintelligence

Online banking has made access to banking services easier than ever for millions of people and in the process reduced the need for an extensive branch network. Patients can also take photos of meals, which are then available for their doctor to view, giving much more insight into patients' lifestyles and potential risks," says Rowan Scranage at Couchbase. "Early applications for AI have spread through many industries, from healthcare where providers are starting to use cognitive analytics to aid in the diagnosis of patients, to consumer products such as Apple's Siri, with varying degrees of success," says Dr Richard Harmon, director of Europe, Middle East and Africa financial services at Cloudera. By making it easier to access banking on the go and present pertinent products to users on mobile, based on extensive customer data, conventional banks can utilise the most user-friendly elements of startup banks.


Google's Research In Artificial Intelligence Helps In Preventing Blindness Caused by Diabetes

@machinelearnbot

Piloting this AI-based diagnosis is Aravind Eye Hospital, the largest eye care provider in India. Aravind Eye Hospital contributed to Google's research by providing images of DR patients. Last year Google published a paper on "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs" at The Jama Network. Microsoft has partnered with Hyderabad-based L V Prasad Eye Institute to launch Microsoft Intelligent Network for Eye care (MINE).


Google's Research In Artificial Intelligence Helps In Preventing Blindness Caused by Diabetes

#artificialintelligence

Piloting this AI-based diagnosis is Aravind Eye Hospital, the largest eye care provider in India. Aravind Eye Hospital contributed to Google's research by providing images of DR patients. Last year Google published a paper on "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs" at The Jama Network. Microsoft has partnered with Hyderabad-based L V Prasad Eye Institute to launch Microsoft Intelligent Network for Eye care (MINE).


IBM, JDRF partnership using machine learning methods to tackle Type 1 diabetes

#artificialintelligence

What the research collaboration will attempt to do is create an entry point in the field of precision medicine -- combining JDRF's connections to research teams around the globe, and its subject matter expertise in T1D research, with the technical capability and computing power of IBM. IBM scientists will look across at least three different data sets and apply machine learning algorithms to help find patterns and factors that may be at play, with the goal of identifying ways that could delay or prevent T1D in children. As a result, JDRF will be in a better position to identify the top predictive risk factors for T1D, cluster patients based on top risk factors, and explore a number of data-driven models for predicting onset. The deep expertise our team has in artificial intelligence applied to healthcare data makes us uniquely positioned to help JDRF unlock the insights hidden in this massive data set and advance the field of precision medicine towards the prevention and management of diabetes."