The risk for poor glycemic control in patients with type 2 diabetes can be predicted with confidence by using machine learning methods, a new study from Finland finds. The most important factors ...
A new tool named T1GRS enables researchers to get more accurate, further-reaching risk scores for the greater population ...
University of Virginia School of Data Science researcher Heman Shakeri has been awarded a major new research grant to lead work at the intersection of machine learning and diabetes care. Shakeri will ...
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