The medicine and healthcare sector has been evolving and advancing very fast. The
advancement has been initiated and shaped by the applications of data-driven, robust, and …

Diabetes mellitus is a widespread chronic metabolic disorder that requires regular blood
glucose level surveillance. Current invasive techniques, such as finger-prick tests, often …

There is a paucity of predictive models for uncontrolled diabetes mellitus. The present study
applied different machine learning algorithms on multiple patient characteristics to predict …

Recent advances in self-supervised learning enabled novel medical AI models, known as
foundation models (FMs) that offer great potential for characterizing health from diverse …

Abstract Background Type-2 Diabetes Mellitus (T2D) is a growing concern worldwide, and
family doctors are called to help diabetic patients manage this chronic disease, also with …

Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG)
forecasting is essential for proactive interventions, playing a crucial role in enhancing the …

Type 1 diabetes mellitus (T1D) patients face daily difficulties in keeping their blood glucose
levels within appropriate ranges. Several techniques and devices, such as flash glucose …

Elevated postprandial glucose levels pose a global epidemic and are crucial in
cardiometabolic disease management and prevention. A major challenge is inter-individual …

Precise and timely forecasting of blood glucose levels is essential for effective diabetes
management. While extensive research has been conducted on Type 1 diabetes mellitus …

Diabetes has become one of the most severe and prevalent chronic diseases, leading to life-
threatening, costly, and disabling consequences and reduced life expectancy. Uncontrolled …