Early Detection of Ureteropelvic Junction Obstruction Using Signal Analysis and Machine Learning: A Dynamic Solution to a Dynamic Problem.

Journal: The Journal of urology
Published Date: Mar 1, 2018

Abstract

PURPOSE: We sought to define features that describe the dynamic information in diuresis renograms for the early detection of clinically significant hydronephrosis caused by ureteropelvic junction obstruction.

Authors

  • Emily S Blum
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, Washington, D. C.; Division of Urology, Children's National Health System, Washington, D. C.
  • Antonio R Porras
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, Washington, D. C.. Electronic address: aporraspe@childrensnational.org.
  • Elijah Biggs
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, Washington, D. C.
  • Pooneh R Tabrizi
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, Washington, D. C.
  • Rachael D Sussman
    Division of Urology, MedStar Georgetown University Hospital, Washington, D. C.
  • Bruce M Sprague
    Division of Urology, Children's National Health System, Washington, D. C.
  • Eglal Shalaby-Rana
    Department of Radiology, Children's National Health System, Washington, D. C.
  • Massoud Majd
    Department of Radiology, Children's National Health System, Washington, D. C.
  • Hans G Pohl
    Division of Urology, Children's National Health System, Washington, D. C.
  • Marius George Linguraru
    Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Medical Center, Washington, DC 20010, USA; Departments of Radiology and Pediatrics, School of Medicine and Health Sciences, George Washington University, Washington, DC 20037, USA.

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