Interpretable machine learning for early predicting the risk of ventilator-associated pneumonia in ischemic stroke patients in the intensive care unit
The RF model is reliable in early identifying high-risk IS patients for VAP. The SHAP method offers clear and intuitive explanations for individual risk assessment. The web-based tool has the potential to improve clinical outcomes by promptly recognizing patients at increased VAP risk and facilitating early intervention, further multicenter prospective studies are required to validate its generalizability and practical utility.
Authors
- Songran Yang (ORCID: https://orcid.org/0000-0002-2490-7091)
- Heshan Cao (ORCID: https://orcid.org/0009-0006-0594-4141)
- Jian‐Jun Wei (ORCID: https://orcid.org/0000-0003-0281-2793)
- Ping Hua
Institutions
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- First Affiliated Hospital of Guangzhou University of Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-05-07
- DOI
- https://doi.org/10.3389/fneur.2025.1513732
- Citations
- 2
- Primary Topic
- Nosocomial Infections in ICU
- Type
- article
- Field-Weighted Citation Impact
- 3.09
Funders
- National Natural Science Foundation of China