Kevin Y Chu1, Daniel E Nassau2, Himanshu Arora1, Soum D Lokeshwar1, Vinayak Madhusoodanan1, Ranjith Ramasamy3. 1. Department of Urology, University of Miami Miller School of Medicine, 1120 NW 14th Street, 15th floor, Miami, FL, 33136, USA. 2. Department of Urology, Lenox Hill Hospital, Zucker School of Medicine at Hofstra/Northwell, New York, NY, USA. 3. Department of Urology, University of Miami Miller School of Medicine, 1120 NW 14th Street, 15th floor, Miami, FL, 33136, USA. Ramasamy@miami.edu.
Abstract
PURPOSE OF REVIEW: The promise of artificial intelligence (AI) in medicine has been widely theorized over the past couple of decades. It has only been with technological advances over the past few years that physicians and computer scientists have started discovering its true clinical potential. Reproductive urology is a sub-discipline that AI could be of great contribution, as current predictive models and subjectivity within the field have several limitations. We review the literature to summarize recent AI applications in reproductive urology. RECENT FINDINGS: Early AI applications in reproductive urology focused on predicting semen parameters based on questionnaires that identify potential environmental factors and/or lifestyle habits impacting male fertility. AI has shown success in predicting the patient subpopulation most likely to need a genetic workup for azoospermia. With recent advances in image processing, automated sperm detection is a reality. Semen analyses, once a laboratory-only diagnostic test, have moved into health consumer homes with the advent of AI. AI's prospects in medicine are considerable and there is strong potential for AI within reproductive urology. Research in identifying the factors that can affect reproductive success either naturally or with assisted reproduction is of paramount importance to move the field forward.
PURPOSE OF REVIEW: The promise of artificial intelligence (AI) in medicine has been widely theorized over the past couple of decades. It has only been with technological advances over the past few years that physicians and computer scientists have started discovering its true clinical potential. Reproductive urology is a sub-discipline that AI could be of great contribution, as current predictive models and subjectivity within the field have several limitations. We review the literature to summarize recent AI applications in reproductive urology. RECENT FINDINGS: Early AI applications in reproductive urology focused on predicting semen parameters based on questionnaires that identify potential environmental factors and/or lifestyle habits impacting male fertility. AI has shown success in predicting the patient subpopulation most likely to need a genetic workup for azoospermia. With recent advances in image processing, automated sperm detection is a reality. Semen analyses, once a laboratory-only diagnostic test, have moved into health consumer homes with the advent of AI. AI's prospects in medicine are considerable and there is strong potential for AI within reproductive urology. Research in identifying the factors that can affect reproductive success either naturally or with assisted reproduction is of paramount importance to move the field forward.