EurekAlert!

A step closer to painless diabetes care: new glucose sensor uses smart materials and machine learning

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 ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
The American Journal of Managed Care

Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
WRIC

UVA research found continuous glucose monitors can predict type 1 diabetes complications

RICHMOND, Va. (WRIC) — A research study from the University of Virginia Center for Diabetes Technology suggests that data from continuous glucose monitors (CGMs) can predict the development of serious ...