Development and Validation of an Interpretable Machine Learning Model for Predicting Venous Thromboembolism（VTE）in Intensive Care Unit (ICU) Patients

Venous thromboembolism remains a leading cause of preventable mortality in intensive care unit (ICU) patients. Existing risk-stratification tools were developed in general medical populations and lack ICU-specific predictors. This study was to develop and validate an interpretable machine learning (ML) model to predict VTE in ICU patients.

NCT Number	NCT07596264
Lead Sponsor	Beijing Tsinghua Chang Gung Hospital
Conditions	Venous Thromboembolism, Prediction Models
Enrollment	12,061 participants
Start Date	2022-01-01
Primary Completion	2025-12-31 (estimated)
Study Completion	2025-12-31 (estimated)
Updated on ClinicalTrials.gov	2026-05-19