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 ...

A machine learning model improves prediction of type 1 diabetes risk compared with a conventional genetic risk model, particularly in people without high-risk human leukocyte antigen haplotypes.

Organic electrochemical transistor (OECT), a powerful tool for chemical and biological sensing, can operate directly in aqueous environment at low voltages, which makes it ideal for wearable and ...

In a recent study published in BMC Medicine, researchers identified diabetic individuals among populations with normal fasting glucose using common physical examination indexes via machine learning ...

Study of Over Three Million Patients for Risk of Type 2 Diabetes Demonstrates Potential for More Advanced Approach to Early Identification Over 60% of U.S. adults have risk factors for type 2 diabetes ...