Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling
Predictive models based on the XGBoost algorithm have good performance in predicting the risk of acute appendicitis progressing to complicated appendicitis, which helps to optimize clinical decision making.
Authors
- Jun Pan (ORCID: https://orcid.org/0000-0002-0341-9953)
- Beibei Xu (ORCID: https://orcid.org/0000-0003-2789-7973)
- Miaomiao Teng
- Jianfu Xia
- Yi‐Hsiang Huang (ORCID: https://orcid.org/0000-0001-5241-5425)
- Sunmeng Chen
Institutions
- Wenzhou Medical University (CN)
- Ruian People's Hospital (CN)
- Wenzhou Central Hospital (CN)
Publication Details
- Journal
- BMC Gastroenterology
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1186/s12876-025-03847-6
- Citations
- 3
- Primary Topic
- Appendicitis Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 6.76