INNOVATIVE TECHNOLOGIES IN THE DIAGNOSIS AND TREATMENT OF INFERTILITY: A COMPREHENSIVE REVIEW
Abstract
Infertility is increasingly recognized as a condition affecting diverse populations and one that requires advanced medical and technological approaches to support effective diagnosis and treatment. In recent years, significant progress in medical sciences and digital technologies has refined the ways infertility is assessed and managed. Contemporary diagnostic methods now include high-resolution imaging, hormonal and genetic testing, microbiome evaluation, and immunological analysis. These advancements enable clinicians to identify reproductive disorders with greater precision.
Artificial intelligence (AI) and robotic systems further support clinical decision-making by improving embryo selection, predicting treatment outcomes, and standardizing laboratory procedures. Advances in assisted reproductive technologies (ART) have expanded therapeutic options for patients who previously had limited chances of achieving pregnancy.
Although technology plays a crucial role in modern infertility care, patient experiences and psychological well-being remain equally important, as treatment can be both emotionally and physically demanding. This review summarizes current knowledge on innovative technologies used in the diagnosis and treatment of infertility and highlights how the continued development of these methods enhances clinical outcomes and patient care.
References
American Society for Reproductive Medicine. (2023). Definition of infertility: A committee opinion. https://www.asrm.org/practice-guidance/practice-committee-documents/definition-of-infertility/
Brannigan, R. E., Hermanson, L., Kaczmarek, J., Kim, S. K., Kirkby, E., & Tanrikut, C. (2024). Updates to male infertility: AUA/ASRM guideline. Journal of Urology. https://doi.org/10.1097/JU.0000000000004180
Bueno-Sánchez, L., Alhambra-Borrás, T., Gallego-Valadés, A., & Garcés-Ferrer, J. (2024). Psychosocial impact of infertility diagnosis and conformity to gender norms on the quality of life of infertile Spanish couples. International Journal of Environmental Research and Public Health, 21(2), 158. https://doi.org/10.3390/ijerph21020158
Carson, S. A., & Kallen, A. N. (2021). Diagnosis and management of infertility: A review. JAMA, 326(1), 65–76. https://doi.org/10.1001/jama.2021.4788
de Santiago, I., & Polanski, L. (2022). Data-driven medicine in the diagnosis and treatment of infertility. Journal of Clinical Medicine, 11(21), 6426. https://doi.org/10.3390/jcm11216426
Findikli, N., Houba, C., Pening, D., & Delbaere, A. (2025). The role of artificial intelligence in female infertility diagnosis: An update. Journal of Clinical Medicine, 14(9), 3127. https://doi.org/10.3390/jcm14093127
Ghorbani, M., Hoseini, F. S., Yunesian, M., Salehin, S., Talebi, S. S., & Keramat, A. (2023). A supportive randomized clinical trial on Iranian infertile women with the history of infertility treatments dropout following unsuccessful ART cycle/s: A study protocol. Heliyon, 9(3), e13838. https://doi.org/10.1016/j.heliyon.2023.e13838
World Health Organization Guideline Development Group. (2025). Recommendations from the WHO guideline for the prevention, diagnosis, and treatment of infertility. Fertility and Sterility. https://doi.org/10.1016/j.fertnstert.2025.11.014
Hussain, A., Abbas, M., Zain-ul-Abideen, Mustafa,G., Lateef,M., Mansoor, A., Raza, Y., Hayat, A. & Hussain Lashari, M. (2025). Innovations and challenges in modern infertility treatment: Bridging technology and psychosocial care. Middle East Fertility Society Journal, 30, 44. https://doi.org/10.1186/s43043-025-00257-2
Jankowska, K., & Słowikowska-Hilczer, J. (2019). Rekomendacje dotyczące postępowania w niepłodności męskiej. Postępy Andrologii Online, 6(1), 21–39. https://doi.org/10.26404/PAO_2353-8791.2019.02
Malina, A. (2024). The social infertility cycle model. Health Psychology Report, 12(3), 183–196. https://doi.org/10.5114/hpr/170986
Mapari, S. A., Shrivastava, D., Bedi, G. N., Pradeep, U., Gupta, A., Kasat, P. R., & Sachani, P. (2024). Revolutionizing reproduction: The impact of robotics and artificial intelligence (AI) in assisted reproductive technology: A comprehensive review. Cureus, 16(6), e63072. https://doi.org/10.7759/cureus.63072
Medenica, S., Zivanovic, D., Batkoska, L., Marinelli, S., Basile, G., Perino, A., Cucinella, G., Gullo, G., & Zaami, S. (2022). The future is coming: Artificial intelligence in the treatment of infertility could improve assisted reproduction outcomes—the value of regulatory frameworks. Diagnostics, 12(12), 2979. https://doi.org/10.3390/diagnostics12122979
Olawade, D., Teke, J., Adeleye, K., Weerasinghe, K., & Maidoki, M. (2025). Artificial intelligence in in-vitro fertilization (IVF): A new era of precision and personalization in fertility treatments. Journal of Gynecology Obstetrics and Human Reproduction, 54(3), 102903. https://doi.org/10.1016/j.jogoh.2024.102903
Orovou, E., Tzimourta, K. D., Tzitiridou-Chatzopoulou, M., Karagiannis, A., Gkrekas, D., & Tzallas, A. T. (2025). Artificial intelligence in assisted reproductive technology: A new era in fertility treatment. Cureus, 17(4), e81568. https://doi.org/10.7759/cureus.81568
Peluso, G., Serrao, M., Urlandini, L., Rago, V., Aquila, S., & Vivacqua, A. (2025). New evidence in male infertility diagnosis: The role of metabolomics. Cells, 14(23), 1886. https://doi.org/10.3390/cells14231886
Rabijewski, M. (2019). Hormonal stimulation of spermatogenesis in men with impaired fertility. Quarterly Journal Fides et Ratio, 39(3), 115–124. https://doi.org/10.34766/fetr.v3i39.125
Radwan, M., Zamkowska, D., Wójcik, D., & Ziółkowski, T. (2017). Stymulacja owulacji. Ginekologia i Perinatologia Praktyczna, 2(1), 1–8. https://doi.org/10.5603/gipp.51009
Saleem Azam, S., Vasudevan, S., Saqib Bukhari, W., Thadhani, J., Tasneem, H., Singh, S., Chijioke, I., Mendes de Freitas, B., Bhagyani Weerasinghe Thammitage, M., & Motwani, J. (2025). Reproductive endocrine disorders: A comprehensive guide to the diagnosis and management of infertility, polycystic ovary syndrome, and endometriosis. Cureus, 17(1), e78222. https://doi.org/10.7759/cureus.78222
Schwerdtfeger, K. L., & Shreffler, K. M. (2009). Trauma of pregnancy loss and infertility for mothers and involuntarily childless women in the contemporary United States. Journal of Loss and Trauma, 14(3), 211–227. https://doi.org/10.1080/15325020802537468
Skweres-Kuchta, M., Skweres, A., Szaruga, E., & Łukaszuk, K. (2025). AI-powered knowledge management and decision support for IVF with PGT: Literature review and model proposal, Knowledge management in medicine (Vol. 16, pp. 328–343). https://doi.org/10.18.276/978-83-8419-053-1-23
World Health Organization. (2025). Infertility. https://www.who.int/news-room/fact-sheets/detail/infertility
World Health Organization. (2025, November 28). WHO issues first global guideline on infertility. https://www.who.int/news/item/28-11-2025-who-issues-first-global-guideline-on-infertility
Wu, Y.-C., Su, E. C.-Y., Hou, J.-H., Lin, C.-J., Lin, K. B., & Chen, C.-H. (2025). Artificial intelligence and assisted reproductive technology: A comprehensive systematic review. Taiwanese Journal of Obstetrics and Gynecology, 64(1), 11–26. https://doi.org/10.1016/j.tjog.2024.10.001
Copyright (c) 2026 Zuzanna Dobrakowska, Marzena Swojnóg, Radosław Swędrak, Jakub Klepacz
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles are published in open-access and licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Hence, authors retain copyright to the content of the articles.
CC BY 4.0 License allows content to be copied, adapted, displayed, distributed, re-published or otherwise re-used for any purpose including for adaptation and commercial use provided the content is attributed.
