Machine learning-based time-to-event survival analysis in pediatric patients with severe sepsis
RandomSurvivalForest demonstrated superior time-to-event prediction performance for pediatric sepsis. The survival analysis approach provides dynamic risk assessment and precise timing for clinical interventions. A web-based prediction calculator was developed to facilitate clinical implementation.
Authors
- Ruyi Cai (ORCID: https://orcid.org/0000-0002-4949-0923)
- Zheng Li (ORCID: https://orcid.org/0000-0002-0433-6842)
- Haiyang Chen (ORCID: https://orcid.org/0000-0002-3667-4256)
- Qianru Huang
Institutions
- Nanjing University of Chinese Medicine (CN)
- Xuzhou Medical College (CN)
- Second People’s Hospital of Huai’an (CN)
- Nanjing Jiangning Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Frontiers in Pediatrics
- Published
- 2025-10-23
- DOI
- https://doi.org/10.3389/fped.2025.1688416
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00