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

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 ...

Researchers at at Massachusetts General Hospital have developed a blood test that examines over 200 proteins to assess an individual’s biological aging rate. According to the research, the test — ...

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 ...

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, ...

The researchers published their findings in the journal Nature Communications.

A new study suggests that an AI-assisted blood test, which measures for biomarkers, could help to identify prediabetes risk earlier.

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...