The increasing prevalence of type 2 diabetes mellitus (T2DM) and its associated health
complications highlight the need to develop predictive models for early diagnosis and …

Objectives We aimed to review the literature regarding the use of machine learning to
predict chronic diseases. Study design This was a systematic review. Methods The searches …

Background This study projects the trend of disease burden and economic burden of
diabetes in 33 Chinese provinces and nationally during 2020–2030 and investigates its …

Fasting blood glucose (FBG) and glycosylated hemoglobin (HbA1c) are key indicators
reflecting blood glucose control in type 2 diabetes mellitus (T2DM) patients. The purpose of …

Objectives We aimed to develop machine learning models and evaluate their performance
in predicting HIV and sexually transmitted infections (STIs) diagnosis based on a cohort of …

Artificial intelligence (AI) algorithms can provide actionable insights for clinical decision-
making and managing chronic diseases. The treatment and management of complex …

Diabetes type 2 remains a pressing worldwide health subject, highlighting the need for
advanced early detection methods. In this study, we performed a comprehensive analysis of …

Background To investigate the association between marriage and the prevalence of
overweight and obesity in China. Methods We conducted cross-sectional and retrospective …

The increasing prevalence of diabetes, high avoidable morbidity and mortality due to
diabetes and diabetic complications, and related substantial economic burden make …

Accurate prediction of blood glucose levels is essential for type 1 diabetes optimizing insulin
therapy and minimizing complications in patients with type 1 diabetes. Using ensemble …