Artificial Intelligence in Reproductive Urology

Kevin Y. Chu, Daniel E. Nassau, Himanshu Arora, Soum D. Lokeshwar, Vinayak Madhusoodanan, Ranjith Ramasamy

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations


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. Summary: 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.

Original languageEnglish (US)
Article number52
JournalCurrent urology reports
Issue number9
StatePublished - Sep 1 2019


  • Artificial intelligence
  • Artificial neural network
  • Machine learning
  • Male-factor infertility
  • Reproductive urology
  • Urology

ASJC Scopus subject areas

  • Urology


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