Development and validation of interpretable machine learning models for postoperative pneumonia prediction
Our study firstly demonstrated that the general linear model based on 5 common variables might predict postoperative pneumonia in the general surgical population.
Authors
- Bingbing Xiang (ORCID: https://orcid.org/0000-0001-8090-762X)
- Shulan Jiao (ORCID: https://orcid.org/0000-0002-2955-4045)
- Y.C. Liu (ORCID: https://orcid.org/0009-0000-2783-5831)
- Mingliang Yi (ORCID: https://orcid.org/0000-0003-4962-1919)
- Wensheng Zhang (ORCID: https://orcid.org/0000-0002-2737-8623)
- Shun Wang (ORCID: https://orcid.org/0000-0001-5305-5134)
Institutions
- Sichuan University (CN)
- Kunming Medical University (CN)
- West China Hospital of Sichuan University (CN)
- First Affiliated Hospital of Chengdu Medical College (CN)
- Chengdu Fifth People's Hospital (CN)
- Chengdu University of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2024-12-11
- DOI
- https://doi.org/10.3389/fpubh.2024.1468504
- Citations
- 4
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- Chengdu University of Traditional Chinese Medicine
- Chengdu University