Teng Ge

Interpretable machine learning model for predicting the ICU readmission of patients after coronary intervention

To develop and validate an interpretable machine learning (ML) model integrated with inflammatory indicators for predicting ICU readmission in patients after coronary intervention (PCI/CABG). We used retrospective data from MIMIC-IV (training, 2196 patients) and MIMIC-III (extern...

Factors associated with venous thromboembolism in ICU patients with sepsis: A retrospective analysis using the MIMIC-IV database

This study used the MIMIC-IV v3.1 database to examine factors associated with venous thromboembolism (VTE) in adult ICU patients with sepsis, excluding those with prior VTE or ICU stays under 48 h. Among 14,784 eligible patients, 1,038 (7.0%) developed VTE during their ICU stay....