Machine learning-based radiomic nomogram from unenhanced computed tomography and clinical data predicts bowel resection in incarcerated inguinal hernia
This innovative radiomic-clinical nomogram has proven to be effective in predicting bowel resection risks in IIH patients and has substantially aided clinical decision-making.
Authors
- Jilin Hu (ORCID: https://orcid.org/0000-0001-7118-4781)
- Shun-Li Liu
- Ling Zhu (ORCID: https://orcid.org/0000-0003-3818-6093)
- Xiaoming Zhou (ORCID: https://orcid.org/0000-0002-6165-9277)
- Dong‐Zhi Li (ORCID: https://orcid.org/0000-0002-4583-6800)
- Ruiqing Liu (ORCID: https://orcid.org/0000-0003-1331-700X)
- Zhibo Wang (ORCID: https://orcid.org/0009-0000-1152-6591)
- Jingnong Liu
Institutions
- Weifang People's Hospital (CN)
Publication Details
- Journal
- World Journal of Gastrointestinal Surgery
- Published
- 2025-05-29
- DOI
- https://doi.org/10.4240/wjgs.v17.i6.106155
- Primary Topic
- Hernia repair and management
- Type
- article
- Field-Weighted Citation Impact
- 0.00