INTRODUCTION: Type 2 diabetes (T2D) is a complex metabolic disorder with significant global health implications. Understanding the molecular mechanisms underlying T2D is crucial for developing effective therapeutic strategies. This study employs sing...
BACKGROUND: Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) d...
The rising prevalence of Type 2 Diabetes (T2D) in Saudi Arabia presents significant healthcare challenges. Estimating the age at onset of T2D can aid early interventions, potentially reducing complications due to late diagnoses. This study, conducted...
Biomedical and environmental sciences : BES
39924156
OBJECTIVE: To establish and validate a novel diabetic retinopathy (DR) risk-prediction model using a whole-exome sequencing (WES)-based machine learning (ML) method.
BMC medical informatics and decision making
39966886
AIMS: Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus. Early identification of individuals at high risk of DPN is essential for successful early intervention. Traditional Chinese medicine (TCM) tongue diagnos...
SUMMARY: Polygenic risk scores (PRSs) hold promise for early disease diagnosis and personalized treatment, but their overall discriminative power remains limited for many diseases in the general population. As a result, numerous novel PRS modeling te...
RATIONALE AND OBJECTIVES: Type 2 diabetes is a known risk factor for vascular disease with an impact on the aorta. The aim of this study was to develop a deep learning framework for quantification of aortic phenotypes from magnetic resonance imaging ...
Neural networks : the official journal of the International Neural Network Society
39929068
Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for people living with type 1 or 2 diabetes, thereby reducing complications and improving quality of life. The state of the art of BG prediction has been ac...
BACKGROUND: Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. Machine learning (ML) systems can enhance DR in community-based screening. However, predictive power models for usability and performance are still being d...
Previous research has established type 2 diabetes mellitus as a significant risk factor for various disorders, adversely impacting human health. While evidence increasingly links type 2 diabetes to cognitive impairment and brain disorders, understand...