Machine learning model for predicting urinary tract infection risk in febrile children under 3 years of age
The ML model constructed in this study can accurately predict UTI risk in febrile children under 3 years of age. The visual decision interpretation achieved through the SHAP framework can assist clinicians in quickly identifying high-risk children.
Authors
- Kuankuan Cen
- Jianxin Sun (ORCID: https://orcid.org/0000-0001-5319-912X)
- L. Ye
- Y.-H. Lu
- Ye Bi
- Jing Chen (ORCID: https://orcid.org/0000-0003-0676-1794)
Institutions
- Ningbo University (CN)
Publication Details
- Journal
- Frontiers in Pediatrics
- Published
- 2025-12-08
- DOI
- https://doi.org/10.3389/fped.2025.1677292
- Primary Topic
- Pediatric Urology and Nephrology Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00