An interpretable machine learning approach to evaluate 30-day mortality risk in patients with community-onset bacteremia
ML revealed risk factors for 30-day mortality, including the Pitt bacteremia score, septic shock, age, pneumonia, and comorbidity, which also had multiple synergistic effects on 30-day mortality.
Authors
- Chun-Te Li
- Ju-Ling Chen
- Chien‐Chou Su (ORCID: https://orcid.org/0000-0001-5046-125X)
- Wen-Liang Lin
- Ching-Lan Cheng (ORCID: https://orcid.org/0000-0001-9258-3239)
- Ching‐Chi Lee (ORCID: https://orcid.org/0000-0002-4949-2742)
Institutions
- National Cheng Kung University Hospital (TW)
- National Cheng Kung University (TW)
Publication Details
- Journal
- Journal of Microbiology Immunology and Infection
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1016/j.jmii.2025.08.017
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Cheng Kung University Hospital