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 ...

Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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, ...

CGMformer is first self-supervised pretrained on CGM data to gain fundamental knowledge of the glucose dynamics, and then applied to a multitude of downstream clinical applications. The extractable ...

The study also highlights the limitations of relying on body mass index (BMI) as a proxy for metabolic health.

A research team led by professor Nan-Hee Kim from Korea University's College of Medicine (Nan-Hee Kim and So-Young Park of Department of Endocrinology and Metabolism; Min-Hee Kim and Jae-Young Kim of ...