Explainable Machine Learning Models Using Routine Clinical Data for Early Prediction of Necrotizing Fasciitis: A Single‐Center Retrospective Study
The XGBoost model facilitates accurate early identification of NF leveraging routine clinical indices. The model's interpretability facilitates clinical decision support systems by providing evidence-based diagnostic workflow optimization.
Authors
- Xu Zheng (ORCID: https://orcid.org/0009-0000-3666-5053)
- Rui Zhang (ORCID: https://orcid.org/0000-0002-8132-6250)
- Qi Han (ORCID: https://orcid.org/0000-0003-0073-4162)
- Guosheng Wang (ORCID: https://orcid.org/0009-0002-4031-6619)
Institutions
- Harbin Medical University (CN)
- First Affiliated Hospital of Harbin Medical University (CN)
Publication Details
- Journal
- ANZ Journal of Surgery
- Published
- 2025-11-24
- DOI
- https://doi.org/10.1111/ans.70395
- Primary Topic
- Streptococcal Infections and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- China Primary Health Care Foundation