Machine learning-based classification of diabetes mellitus using sociodemographic, behavioral, and clinical predictor

Researchers have developed machine learning models to improve the prediction of diabetes mellitus in low- and middle-income countries using sociodemographic and clinical data. The study found that ensemble methods, particularly XGBoost, provided the most accurate risk assessments for early intervention.