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 article

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. 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
Volume20
Issue number9
DOIs
StatePublished - Sep 1 2019

Fingerprint

Artificial Intelligence
Urology
Medicine
Azoospermia
Semen Analysis
Semen
Routine Diagnostic Tests
Habits
Reproduction
Fertility
Spermatozoa
Life Style
Physicians
Health
Research

Keywords

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

ASJC Scopus subject areas

  • Urology

Cite this

Chu, K. Y., Nassau, D. E., Arora, H., Lokeshwar, S. D., Madhusoodanan, V., & Ramasamy, R. (2019). Artificial Intelligence in Reproductive Urology. Current Urology Reports, 20(9), [52]. https://doi.org/10.1007/s11934-019-0914-4

Artificial Intelligence in Reproductive Urology. / Chu, Kevin Y.; Nassau, Daniel E.; Arora, Himanshu; Lokeshwar, Soum D.; Madhusoodanan, Vinayak; Ramasamy, Ranjith.

In: Current Urology Reports, Vol. 20, No. 9, 52, 01.09.2019.

Research output: Contribution to journalReview article

Chu, KY, Nassau, DE, Arora, H, Lokeshwar, SD, Madhusoodanan, V & Ramasamy, R 2019, 'Artificial Intelligence in Reproductive Urology', Current Urology Reports, vol. 20, no. 9, 52. https://doi.org/10.1007/s11934-019-0914-4
Chu KY, Nassau DE, Arora H, Lokeshwar SD, Madhusoodanan V, Ramasamy R. Artificial Intelligence in Reproductive Urology. Current Urology Reports. 2019 Sep 1;20(9). 52. https://doi.org/10.1007/s11934-019-0914-4
Chu, Kevin Y. ; Nassau, Daniel E. ; Arora, Himanshu ; Lokeshwar, Soum D. ; Madhusoodanan, Vinayak ; Ramasamy, Ranjith. / Artificial Intelligence in Reproductive Urology. In: Current Urology Reports. 2019 ; Vol. 20, No. 9.
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