Diabetes


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

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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

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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

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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

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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

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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."


IBM partners to identify risk factors for Type I diabetes – MassDevice

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IBM (NYSE:IBM) plans to develop and apply machine learning techniques to years of research data in the hopes of identifying factors that trigger the onset of Type I diabetes in children, with the support of JDRF. Scientists at IBM are slated to assess three different data sets using machine learning algorithms to find patterns and factors that could one day help delay or prevent Type I diabetes. Get the full story at our sister site, Drug Delivery Business News.


IBM aims machine learning at type 1 diabetes with JDRF partnership

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The partnership is meant to give type 1 diabetes a foothold in emerging precision medicine efforts, officials say, combining JDRF's global research with the computing power of IBM. The models that emerge should quantify the risk for juvenile diabetes from the combined dataset using this foundational set of features, officials say. That will enable JDRF to better identify top predictive risk factors, cluster patients based on them and explore a number of data-driven models for predicting onset. A bit further on, the partners have eyes toward putting big data to work helping understand root causes of type 1 diabetes and hope to apply analytics to more complex datasets, such as microbiome and genomics or transcriptomics data.


Diagnosing the future of health apps

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Whether being used by organisations to adapt and streamline processes to improve data access and patient care or by patients themselves looking at ways to better understand and manage their health, the sector is set to be transformed by the evolution of apps. The findings include important trends that will affect the future of healthcare, including artificial intelligence and how embeddables (i.e. With the number of people with diabetes in Europe forecast to rise from 59.8 million in 2015 to 71.1 million in 2040, such apps have the potential to make a dramatic impact by putting sophisticated healthcare into the hands of the patient. I believe the need for greater transparency, combined with emerging business models and processes, will drive more people to call for the healthcare industry to safeguard data and improve overall application security standards.


Artificial Intelligence Shows Potential to Fight Blindness

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This advance has the potential to reduce the worldwide rate of vision loss due to diabetes. In a study published online in Ophthalmology, the journal of the American Academy of Ophthalmology, the researchers describe how they used deep-learning methods to create an automated algorithm to detect diabetic retinopathy. Dr. Leng's algorithm could identify all disease stages, from mild to severe, with an accuracy rate of 94 percent. This is why an effective, automated algorithm could potentially reduce the rate of worldwide blindness.


Artificial intelligence in health care: Better studies are needed

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An article in Newsweek magazine says, "Artificial intelligence will cure America's sick health care system" using data and automation to "drive down the costs of health care while increasing effectiveness." A company called Virta Health has come up with a smartphone app that is like "a live-in doctor and diabetes coach." The patient population consisted of 238 morbidly obese patients with type 2 diabetes; 90 percent were taking one or more diabetes medications, and 80 percent had hemoglobin A1c levels 6.5 percent. We are going to need a better study with randomized patients and a much longer follow-up period before we can say artificial intelligence is going to "cure America"s sick health care system."