Deep learning for prognostic stratification and biomarker exploration in upper tract urothelial carcinoma: a multicenter retrospective cohort study
This prior knowledge-guided deep learning system significantly improves OS prediction and risk stratification in UTUC by integrating multiscale pathological features. The AI-driven, interpretable tool offers an objective approach for prognostic assessment and biomarker discovery, with strong potential to refine personalized UTUC management and enhance prognostic accuracy.
Authors
- Wenlong Zhao (ORCID: https://orcid.org/0000-0002-6002-7091)
- Youde Cao (ORCID: https://orcid.org/0000-0002-5961-9196)
- Mingzhao Xiao (ORCID: https://orcid.org/0000-0001-6989-5971)
- Yiwen Tan
- Xiang Peng
- Hao Tan (ORCID: https://orcid.org/0000-0002-3447-6600)
- Weiyang He (ORCID: https://orcid.org/0000-0002-5265-7595)
- X. Liu (ORCID: https://orcid.org/0000-0003-1366-5530)
- Bangxin Xiao
- Bing Liang (ORCID: https://orcid.org/0000-0002-9268-4512)
- Xiaofeng Yue (ORCID: https://orcid.org/0000-0003-0695-7842)
- Quanhao He (ORCID: https://orcid.org/0000-0002-8231-8199)
Institutions
- Dalian Medical University (CN)
- Second Affiliated Hospital of Chongqing Medical University (CN)
- Third People 's Hospital of Chongqing (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Emergency Medical Center (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2025-10-03
- DOI
- https://doi.org/10.1097/js9.0000000000003581
- Primary Topic
- Bladder and Urothelial Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00