An Artificial Intelligence System for the Detection of Bladder Cancer via Cystoscopy: A Multicenter Diagnostic Study

Abstract Background Cystoscopy plays an important role in bladder cancer (BCa) diagnosis and treatment, but its sensitivity needs improvement. Artificial intelligence has shown promise in endoscopy, but few cystoscopic applications have been reported. We report a Cystoscopy Artificial Intelligence D...

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Veröffentlicht in:	JNCI : Journal of the National Cancer Institute 2022-02, Vol.114 (2), p.220-227
Hauptverfasser:	Wu, Shaoxu, Chen, Xiong, Pan, Jiexin, Dong, Wen, Diao, Xiayao, Zhang, Ruiyun, Zhang, Yonghai, Zhang, Yuanfeng, Qian, Guang, Chen, Hao, Lin, Haotian, Xu, Shizhong, Chen, Zhiwen, Zhou, Xiaozhou, Mei, Hongbing, Wu, Chenglong, Lv, Qiang, Yuan, Baorui, Chen, Zeshi, Liao, Wenjian, Yang, Xuefan, Chen, Haige, Huang, Jian, Lin, Tianxin
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial intelligence Bladder Bladder cancer Cancer Confidence intervals Diagnosis Diagnostic systems Endoscopy Latency Medical diagnosis Sensitivity Transfer learning Urology
Online-Zugang:	Volltext
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