When Arinze Nkemdirim Okere, PharmD, MBA, worked as the pharmacist for a hospital in Tallahassee, Florida, he noticed that ...

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

1 Department of Endocrinology, Hainan Provincial People’s Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China 2 Department of Medical Record Management, Hainan ...

Introduction: This study aimed to develop a diabetic retinopathy (DR) Prediction model using various machine learning algorithms incorporating the novel predictor Triglyceride-glucose index (TyG).

Introduction: Non-contrast computed tomography calcium scoring (CTCS) provides a direct, noninvasive measure of atherosclerotic plaque burden by detecting calcified lesions in the coronary arteries.

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, ...

Introduction: Early identification of pregnant women at risk of hypertensive disorders of pregnancy (HDP) is critical for improving pregnancy outcomes. The USPSTF risk stratification approach ...

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...