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 H. Maier‐Hein,Mirabela Rusu,Olivier Rouvière,Roderick van den Bergh,Valeria Panebianco,Veeru Kasivisvanathan,Nancy A. Obuchowski,Derya Yakar,Mattijs Elschot,Jeroen Veltman,Jurgen J. Fütterer,Maarten de Rooij,Henkjan Huisman
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.