This overview examines the integration of machine learning (ML) approaches into diabetes prediction and diagnosis, highlighting the evolution from classical statistical methods to advanced data-driven ...

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, ...

Google has been busy recently. Just in the past week it has closed down its Google Fit website, launched a new drug disposal tool and announced the first clinical use of Verily’s machine learning tool ...

By Hugo Francisco de Souza A new study shows that gut microbiome signatures, analyzed through advanced machine learning, can help identify individuals with more severe insulin resistance, offering ...

IBM and JDRF, a global organization funding Type 1 diabetes research, are joining forces. The collaboration will develop machine learning methods and use them to analyze years of Type 1 research data ...

Children’s Mercy Kansas City (Mo.) and Boston-based Joslin Diabetes Center will deploy predictive models for Type 1 diabetes management using technology from Cambridge, Mass.-based Cyft. Cyft ...

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

Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - is one of the fundamental causes of diabetes. In addition to diabetes, it is ...

Insulin resistance—when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels—is one of the fundamental causes of diabetes. In addition to diabetes, it is ...

The researchers published their findings in the journal Nature Communications.