This overview examines the integration of machine learning (ML) approaches into diabetes prediction and diagnosis, highlighting the evolution from classical statistical methods to advanced data-driven ...
Combining wearable-derived daily step counts with polygenic risk scores improves the prediction of incident type 2 diabetes ...
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, ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
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