Development and validation of an interpretable Random Forest model for predicting recurrence after endoscopic submucosal dissection in superficial oesophageal squamous cell carcinoma
This study successfully developed and validated an explainable RF-based machine learning model to accurately predict recurrence risk in SESCC patients after ESD.
Authors
- Y. D. Yang (ORCID: https://orcid.org/0009-0008-9752-3049)
- Ping Sun (ORCID: https://orcid.org/0000-0002-5376-5264)
- H. Zhu
- Shuo Li (ORCID: https://orcid.org/0000-0003-2331-2448)
- Xinyan Li (ORCID: https://orcid.org/0009-0007-1408-9164)
- Zhenghui Zhu (ORCID: https://orcid.org/0000-0003-4603-7725)
- W. Chen
- Guoqin Zhu
- Qinghua Li
Institutions
- Jiangsu Province Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2025-12-24
- DOI
- https://doi.org/10.1080/07853890.2025.2606571
- Citations
- 1
- Primary Topic
- Esophageal Cancer Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.01