Survival Prediction for Postoperative Patients With Kidney Cancer Based on Computed Tomography Radiomics: Retrospective Cohort Study
Our radiomics nomogram successfully integrates CT-derived radiomic features with clinical variables for kidney cancer survival prediction, demonstrating good prognostic capability and offering a noninvasive, quantitative tool for personalized postoperative management and clinical decision-making.
Authors
- Li‐Wen Lai
- Guoqing He
- Haowen Pang (ORCID: https://orcid.org/0000-0003-4877-9343)
- Huaiwen Zhang (ORCID: https://orcid.org/0000-0001-6259-6426)
- Xiaohui Yu
- Y. Lv
- Qingxiu Zhu
- Guan Yu Yu
Institutions
- Affiliated Hospital of Southwest Medical University (CN)
- Jiangxi Provincial Cancer Hospital (CN)
- Jingdezhen University (CN)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-10-21
- DOI
- https://doi.org/10.2196/73162
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36