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◆ Radiology Imaging Cancer2026-04-10· Medicine

Evaluating an AI-driven Triaging Workflow for MRI-based Clinically Significant Prostate Cancer Diagnosis: A Simulation Study

Jasper J. Twilt, Anindo Saha, Joeran S. Bosma, Gianluca Giannarini, Anwar R. Padhani, Derya Yakar, Mattijs Elschot, Jeroen Veltman, Jurgen J. Fütterer, H. J. Huisman, Maarten de Rooij, Anindo Saha, Joeran S. Bosma, Jasper J. Twilt, Bram van Ginneken, Constant R. Noordman, Ilse Slootweg, Christian Roest, Stefan J. Fransen, Mohammed R. S. Sunoqrot, Tone F. Bathen, Dennis B. Rouw, Jos Immerzeel, Jeroen Geerdink, Chris van Run, Miriam Groeneveld, James Meakin, Derya Yakar, Mattijs Elschot, Jeroen Veltman, Jurgen J. Fütterer, Maarten de Rooij, H. J. Huisman, Anders Bjartell, Anwar R. Padhani, David Bonekamp, Geert Villeirs, Georg Salomon, Gianluca Giannarini, H. J. Huisman, Jayashree Kalpathy-Cramer, Jelle Barentsz, Klaus H. Maier-Hein, Mattijs Elschot, Mirabela Rusu, Nancy A. Obuchowski, Olivier Rouvière, Roderick van den Bergh, Valeria Panebianco, Veeru Kasivisvanathan, Ahmet Karagöz, Alexandre Bône, Alexandre Routier, Arnaud Marcoux, Clément Abi-Nader, Cynthia Li, Dagan Feng, Deniz Alış, Ercan Karaarslan, Euijoon Ahn, François Nicolas, Geoffrey A. Sonn, Indrani Bhattacharya, Jinman Kim, Jun Shi, Hassan Jahanandish, Hong An, Hongyu Kan, Ilkay Oksuz, Liang Qiao, Marc-Michel Rohé, Mert Yergin, Mirabela Rusu, Mohamed Khadra, Mustafa Ege Şeker, Mustafa Said Kartal, Noëlie Debs, Richard E. Fan, Sara Saunders, Simon John Christoph Soerensen, Stefania Moroianu, Sulaiman Vesal, Yuan Yuan, Afsoun Malakoti-Fard, Agnė Mačiūnien, Akira Kawashima, Ana M. M. de M. G. de Sousa Machadov, Ana Sofia L. Moreira, Andrea Ponsiglione, Annelies Rappaport, Arnaldo Stanzione, Arturas Ciuvasovas, Baris Turkbey, Bart De Keyzer, Bodil Ginnerup Pedersen, Bram Eijlers, Christine Chen, Ciabattoni Riccardo, Deniz Alış, Ewout F.W. Courrech Staal

原始摘要(英文原文)· Original abstract
A simulated artificial intelligence–driven triaging workflow for clinically significant prostate cancer diagnosis at MRI triaged 49% of examinations, improving specificity while maintaining radiologist-level sensitivity.
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Evaluating an AI-driven Triaging Workflow for MRI-based Clinically Significant Prostate Cancer Diagnosis: A Simulation Study — 科研速览 Science Skim