Deep Learning for Predicting Difficulty in Radical Prostatectomy: A Novel Evaluation Scheme.

Journal: Urology
PMID: 39814211

Abstract

OBJECTIVE: To explore new metrics for assessing radical prostatectomy difficulty through a two-stage deep learning method from preoperative magnetic resonance imaging.

Authors

  • Haonan Mei
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430060, China; Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430060, China.
  • Zhongyu Wang
    a Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology , Dalian University of Technology , Dalian , China.
  • Qingyuan Zheng
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Panpan Jiao
    Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-Dong Road, Wuhan, 430060, Hubei, People's Republic of China.
  • Jiejun Wu
    Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-Dong Road, Wuhan, 430060, Hubei, People's Republic of China.
  • Xiuheng Liu
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Rui Yang
    Department of Biomedical Informatics, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.

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