Machine learning prediction of ARDS after heart valve surgery: development and validation in Northwest China
The XGBoost model accurately predicts ARDS risk following CPB-assisted HVR using six clinically relevant predictors, providing a valuable tool for early risk stratification and potential intervention in high-risk patients.
Authors
- Hao Chen (ORCID: https://orcid.org/0000-0003-3074-2235)
- Xuhua Li
- Qiyuan Bai (ORCID: https://orcid.org/0009-0008-6135-8950)
- Hengxi Zhang
- Bing Song
- Aoxiang Chen
- Wenhao Zhan
- Yalan Zhang
Institutions
- First Hospital of Lanzhou University (CN)
- Razi Hospital (IR)
- Lanzhou University (CN)
- Xi'an Jiaotong University (CN)
- University of Science and Technology Beijing (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2026-01-21
- DOI
- https://doi.org/10.3389/fcvm.2025.1696326
- Primary Topic
- Cardiac and Coronary Surgery Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Lanzhou University