Combination of deep learning and ensemble machine learning using intraoperative video images strongly predicts recovery of urinary continence after robot-assisted radical prostatectomy.

Journal: Cancer reports (Hoboken, N.J.)
Published Date: Jul 14, 2023

Abstract

BACKGROUND: We recently reported the importance of deep learning (DL) of pelvic magnetic resonance imaging in predicting the degree of urinary incontinence (UI) following robot-assisted radical prostatectomy (RARP). However, our results were limited because the prediction accuracy was approximately 70%.

Authors

  • Wataru Nakamura
    Department of Urology, School of Medicine, Fujita Health University, Toyoake, Japan.
  • Makoto Sumitomo
    Department of Urology, Fujita Health University School of Medicine, Toyoake, Japan.
  • Kenji Zennami
    Department of Urology, Fujita Health University School of Medicine, Toyoake, Japan.
  • Masashi Takenaka
    Department of Urology and School of Medicine, Fujita Health University, Toyoake, Japan.
  • Manabu Ichino
    Department of Urology, Fujita Health University School of Medicine, Toyoake, Japan.
  • Kiyoshi Takahara
    Department of Urology, Fujita Health University School of Medicine, Toyoake, Japan.
  • Atsushi Teramoto
    Faculty of Radiological Technology, School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi 470-1192, Japan.
  • Ryoichi Shiroki
    Department of Urology, Fujita Health University School of Medicine, Toyoake, Japan.

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