Liquid biopsy based on multi-targeted capture of urinary tumor DNA combined with machine learning to detect urothelial carcinoma: a multicenter prospective study.

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Bibliographic Details
Title: Liquid biopsy based on multi-targeted capture of urinary tumor DNA combined with machine learning to detect urothelial carcinoma: a multicenter prospective study.
Authors: Tang C; Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China., Wang T; Department of Urology, Shanghai Eighth People's Hospital, Shanghai, 200235, China., Luo H; Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China., Xue J; Department of Urology, Shanghai Eighth People's Hospital, Shanghai, 200235, China. xuejingdong@126.com.; Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China. xuejingdong@126.com., Zhu M; Shanghai Biovuetech Co., Ltd, Shanghai, 200063, China., Hong Z; Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China., Ding F; Physical Examination Center, Shanghai Eighth People's Hospital, Shanghai, 200235, China., Zhang F; Shanghai Biovuetech Co., Ltd, Shanghai, 200063, China., Zhu Y; Shanghai Biovuetech Co., Ltd, Shanghai, 200063, China., Tan R; Shanghai Biovuetech Co., Ltd, Shanghai, 200063, China. roy.tan@biovuetech.cn., Wu D; Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China. wudenglong2009@tongji.edu.cn.
Source: International urology and nephrology [Int Urol Nephrol] 2026 Apr; Vol. 58 (4), pp. 1291-1306. Date of Electronic Publication: 2025 Sep 25.
Publication Type: Journal Article; Multicenter Study
Journal Info: Publisher: Springer Country of Publication: Netherlands NLM ID: 0262521 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-2584 (Electronic) Linking ISSN: 03011623 NLM ISO Abbreviation: Int Urol Nephrol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1573-2584
DOI:10.1007/s11255-025-04813-7