A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study
This study developed the first radiomics-clinical random forest model for the preoperative prediction of DLC by machine learning algorithms. This predictive model supports safer and individualized surgical planning and treatment strategies.
Authors
- Weiyu Hu (ORCID: https://orcid.org/0000-0001-6480-7979)
- Yu Jiang (ORCID: https://orcid.org/0000-0001-9454-1796)
- Jingyu Cao (ORCID: https://orcid.org/0000-0003-0508-1279)
- Xiaonan Yang (ORCID: https://orcid.org/0009-0002-8428-1681)
- Wenkun Bai (ORCID: https://orcid.org/0000-0002-4334-9945)
- Chao Qu (ORCID: https://orcid.org/0000-0002-6313-5688)
- Jiufa Cui
- Changlei Li
- Kun Li (ORCID: https://orcid.org/0000-0001-7054-0756)
- Ruitao Sun
- Kui Liu (ORCID: https://orcid.org/0000-0002-7493-2244)
- Bin Tan
- Ao-Yun Hao
Institutions
- Qingdao University (CN)
- Affiliated Hospital of Qingdao University (CN)
Publication Details
- Journal
- World Journal of Emergency Surgery
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1186/s13017-025-00635-1
- Citations
- 6
- Primary Topic
- Gallbladder and Bile Duct Disorders
- Type
- article
- Field-Weighted Citation Impact
- 9.11
Funders
- Taishan Scholar Foundation of Shandong Province
- Natural Science Foundation of Shandong Province
- Natural Science Foundation of Qingdao