A novel multi-task XGBoost model shows robust overall performance in predicting antimicrobial resistance in common gram-negative pathogens.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

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 ...

The importance of immune cell types in the XGBoost model. The influence of immune cell infiltration scores on SHAP values, with a color gradient representing low to high cell infiltration scores.