REVIEW article
Front. Urol.
Sec. Male Urology
This article is part of the Research TopicArtificial Intelligence and Male InfertilityView all articles
Breaking Barriers in Male Infertility: the power of artificial intelligence driven solutions
Provisionally accepted
Laura Ibañez Vazquez1*
Natalia Pérez Romero1*
Daniel Tueti Silva1Sarelis Infante1Claudia González Santander1
Irene De La Parra2Isabel Galante Romo1Juan A Gómez Rivas1Jesús Moreno Sierra1- 1San Carlos University Clinical Hospital, Madrid, Spain
- 2Hospital Universitario Ramon y Cajal, Madrid, Spain
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Infertility is defined as the inability of a sexually active couple, not using contraception, to achieve a spontaneous pregnancy within 12 months. It affects an estimated 8% to 12% of couples worldwide, with 30 to 50% of cases attributable, either primarily or in part, to male factors. Despite the increasing number of assisted reproductive technology (ART) procedures performed globally, improvements in fertilization and pregnancy outcomes have been limited. The need to improve diagnostic accuracy and therapeutic efficiency has driven the development of artificial intelligence (AI) in reproductive medicine. This narrative review aims to explore how AI is transforming the diagnosis and treatment of male infertility. AI technologies are nowadays being used to automate and refine semen analysis, providing more reliable assessments of sperm morphology, motility, and concentration. These innovations enable clinicians to improve the prediction of semen quality and to identify which patients might benefit most from specific interventions, such as sperm retrieval in cases of non-obstructive azoospermia or the selection of optimal sperm cells for reproductive techniques. Moreover, advanced AI algorithms —including support vector machines, deep neural networks, and decision trees— outperform traditional methods, offering greater precision and reducing subjectivity in laboratory evaluations. Additionally, AI is being utilized to estimate the chances of success with assisted reproductive techniques, assess sperm DNA fragmentation, and guide the selection of sperm. The integration of AI into clinical practice not only enables more accessible and personalized diagnoses but also opens new perspectives for the development of individualized treatments, optimizing reproductive outcomes. However, further multicentred validation of AI-based models, methodological standardization, and careful consideration of ethical and privacy issues are necessary before widespread clinical adoption.
Keywords: Artificail Intelligence, male infertility, predictive models of ART, Semen analyses, semen diagnostic evaluation
Received: 07 Oct 2025; Accepted: 26 Jan 2026.
Copyright: © 2026 Ibañez Vazquez, Pérez Romero, Tueti Silva, Infante, González Santander, De La Parra, Galante Romo, Gómez Rivas and Moreno Sierra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Laura Ibañez Vazquez
Natalia Pérez Romero
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.