“XGBoost Machine Learning Model for Early Accurate Prediction of Pulmonary Embolism Using Accessible Patient Data”

https://pubmed.ncbi.nlm.nih.gov/38113803

This study established an XGBoost machine learning model that accurately predicts pulmonary embolism at an early stage using accessible patient data, with a low missed diagnosis rate and high AUC value, offering a potential tool for early detection and reducing the burden of misdiagnosis.