前列腺癌
医学
癌症检测
前列腺
医学物理学
癌症
核医学
内科学
作者
Anindo Saha,Joeran Sander Bosma,Jasper Jonathan Twilt,Bram van Ginneken,Anders Bjartell,Anwar R. Padhani,David Bonekamp,Geert Villeirs,Georg Salomon,Gianluca Giannarini,Jayashree Kalpathy–Cramer,Jelle O. Barentsz,Klaus Maier‐Hein,Mirabela Rusu,Olivier Rouvière,Roderick van den Bergh,Valeria Panebianco,Veeru Kasivisvanathan,Nancy A. Obuchowski,Derya Yakar
出处
期刊:Lancet Oncology
[Elsevier BV]
日期:2024-06-12
卷期号:25 (7): 879-887
被引量:40
标识
DOI:10.1016/s1470-2045(24)00220-1
摘要
Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale.
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