Improved early prediction of acute pancreatitis severity using SHAP-based XGBoost model: Beyond traditional scoring systems
The proposed SHAP-enhanced XGBoost model offers a reliable and interpretable tool for early prediction of AP severity, improving clinical decision-making and patient management.
Authors
- María Lourdes Ruiz Rebollo (ORCID: https://orcid.org/0000-0003-4600-9257)
- Ana Cisnal (ORCID: https://orcid.org/0000-0002-1556-7179)
- Javier Pérez Turiel (ORCID: https://orcid.org/0000-0002-7731-2411)
- Juan Carlos Fraile (ORCID: https://orcid.org/0000-0002-2877-7300)
- Jessica Matesanz-Isabel
- César Flórez-Pardo
Institutions
- Universidad de Valladolid (ES)
- Instituto de Estudios de Ciencias de la Salud de Castilla y León (ES)
- Hospital Clínico Universitario de Valladolid (ES)
Publication Details
- Journal
- Digestive and Liver Disease
- Published
- 2025-11-08
- DOI
- https://doi.org/10.1016/j.dld.2025.10.017
- Citations
- 2
- Primary Topic
- Pancreatitis Pathology and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.01