Assessing the Performance of Artificial Intelligence Assistance for Prostate MRI: A Two-Center Study Involving Radiologists With Different Experience Levels.

Journal: Journal of magnetic resonance imaging : JMRI
PMID:

Abstract

BACKGROUND: Artificial intelligence (AI) assistance may enhance radiologists' performance in detecting clinically significant prostate cancer (csPCa) on MRI. Further validation is needed for radiologists with different experiences.

Authors

  • Zhaonan Sun
    Department of Radiology, Peking University First Hospital, 8, Xishiku Street, Xicheng District, Beijing, 100034, China.
  • Kexin Wang
    Clifford Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Ge Gao
    School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou 213000, China.
  • Huihui Wang
    School of Mechanical Engineering & Automation, Dalian Polytechnic University, Qinggongyuan 1, Ganjingzi District, Dalian 116034, PR China; National Engineering Research Center of Seafood, Dalian Polytechnic University, Qinggongyuan 1, Ganjingzi District, Dalian 116034, PR China; Engineering Research Center of Seafood of Ministry of Education of China, Dalian 116034, PR China; Collaborative Innovation Center of Seafood Deep Processing, Dalian 116034, PR China. Electronic address: wanghh@dlpu.edu.cn.
  • Pengsheng Wu
    Beijing Smart Tree Medical Technology Co. Ltd, Beijing, China.
  • Jialun Li
    Beijing Smart Tree Medical Technology Co. Ltd., Beijing, 100011, China.
  • Xiaodong Zhang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • XiaoYing Wang