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 ...

This study highlights the potential for using deep learning methods on longitudinal health data from both primary and ...

In people with type 1 diabetes (T1D), the immune system shuts down the body's ability to make the hormone insulin, ...

Whether estimating the probability that a disease is present or forecasting risk of deterioration,1 readmission,2 or death,3 most contemporary clinical artificial intelligence (AI) systems are ...

A new study shows that gut microbiome signatures, analyzed through advanced machine learning, can help identify individuals with more severe insulin resistance, offering fresh insight into the ...

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 ...

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, ...