Development and validation of risk prediction models for high-risk patients with non-traumatic acute abdominal pain: a prospective observational study
Machine learning models were developed for early risk prediction in non-traumatic acute abdominal pain; random forest showed the best discrimination, while logistic regression with a nomogram offered superior clinical applicability.
Authors
- Yan Yang (ORCID: https://orcid.org/0000-0002-5662-4600)
- Xiaohui Wei (ORCID: https://orcid.org/0000-0001-5086-0103)
- Dannan Ai
- Lijin Zhou (ORCID: https://orcid.org/0000-0002-6960-5951)
- Rui Li (ORCID: https://orcid.org/0000-0001-8845-424X)
- Xiaoqin Li (ORCID: https://orcid.org/0000-0003-3762-9817)
- Aihua Dong
Institutions
- Shanghai Jiao Tong University (CN)
- Renji Hospital (CN)
- Soochow University (CN)
- Tongren Hospital (CN)
- Shanghai Pulmonary Hospital (CN)
- First Affiliated Hospital of Soochow University (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-12-09
- DOI
- https://doi.org/10.3389/fpubh.2025.1701050
- Primary Topic
- Appendicitis Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Suzhou University