Feasibility of a deep learning-based diagnostic platform to evaluate lower urinary tract disorders in men using simple uroflowmetry.

Journal: Investigative and clinical urology
Published Date: Mar 25, 2022

Abstract

PURPOSE: To diagnose lower urinary tract symptoms (LUTS) in a noninvasive manner, we created a prediction model for bladder outlet obstruction (BOO) and detrusor underactivity (DUA) using simple uroflowmetry. In this study, we used deep learning to analyze simple uroflowmetry.

Authors

  • Seokhwan Bang
    Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Sokhib Tukhtaev
    Medical AI Research Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Kwang Jin Ko
    Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Deok Hyun Han
    Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Minki Baek
    Department of Surgery, Division of Pediatric Urology, Texas Children's Hospital, Houston, TX, USA; Scott Department of Urology, Baylor College of Medicine, Houston, TX, USA.
  • Hwang Gyun Jeon
    Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Baek Hwan Cho
    Smart Healthcare & Device Research Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
  • Kyu-Sung Lee
    Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul 06351, South Korea; Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, South Korea. Electronic address: ks63.lee@samsung.com.

Keywords

External Resources

Popular Topics
Recent Journals