Artificial Intelligence in Pediatric Urology.

Journal: The Urologic clinics of North America
Published Date:

Abstract

Application of artificial intelligence (AI) is one of the hottest topics in medicine. Unlike traditional methods that rely heavily on statistical assumptions, machine learning algorithms can identify highly complex patterns from data, allowing robust predictions. There is an abundance of evidence of exponentially increasing pediatric urologic publications using AI methodology in recent years. While these studies show great promise for better understanding of disease and patient care, we should be realistic about the challenges arising from the nature of pediatric urologic conditions and practice, in order to continue to produce high-impact research.

Authors

  • Hsin-Hsiao Scott Wang
    Department of Urology, Boston Children's Hospital (Advanced Analytics Group of Pediatric Urology), Boston, Massachusetts.
  • Ranveer Vasdev
    Department of Urology, University of Minnesota, Minneapolis, Minnesota, USA.
  • Caleb P Nelson
    Clinical and Health Services Research, Department of Urology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, USA.