Development and validation of an artificial intelligence-based model for detecting urothelial carcinoma using urine cytology images: a multicentre, diagnostic study with prospective validationResearch in context

Summary: Background: Urine cytology is an important non-invasive examination for urothelial carcinoma (UC) diagnosis and follow-up. We aimed to explore whether artificial intelligence (AI) can enhance the sensitivity of urine cytology and help avoid unnecessary endoscopy. Methods: In this multicent...

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Hauptverfasser:	Shaoxu Wu, Runnan Shen, Guibin Hong, Yun Luo, Huan Wan, Jiahao Feng, Zeshi Chen, Fan Jiang, Yun Wang, Chengxiao Liao, Xiaoyang Li, Bohao Liu, Xiaowei Huang, Kai Liu, Ping Qin, Yahui Wang, Ye Xie, Nengtai Ouyang, Jian Huang, Tianxin Lin
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2024-05-01
Schriftenreihe:	EClinicalMedicine
Schlagworte:	Artificial intelligence Urine cytology Urothelial carcinoma Multicentre study Prospective validation
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2589537024001457
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