par Findikli, Necati;Houba, Catherine;Pening, David 
;Delbaere, Anne
Référence Journal of Clinical Medicine, 14, 9, page (3127)
Publication Publié, 2025-04-30
;Delbaere, Anne Référence Journal of Clinical Medicine, 14, 9, page (3127)
Publication Publié, 2025-04-30
Article révisé par les pairs
| Résumé : | Female infertility is a multifaceted condition affecting millions of women worldwide, with causes ranging from hormonal imbalances and genetic predispositions to lifestyle and environmental factors. Traditional diagnostic approaches, such as hormonal assays, ultrasound imaging, and genetic testing, often require extensive time, resources, and expert interpretation. In recent years, artificial intelligence (AI) has emerged as a transformative tool in the field of reproductive medicine, offering advanced capabilities for improving the accuracy, efficiency, and personalization of infertility diagnosis and treatment. AI technologies demonstrate significant potential in analyzing vast and complex datasets, identifying hidden patterns, and providing data-driven insights that enhance clinical decision-making processes in assisted reproductive technologies (ART) services. This narrative review explores the current advancements in AI applications in female infertility diagnostics and therapeutics, highlighting key technological innovations, their clinical implications, and existing limitations. It also discusses the future potential of AI in revolutionizing reproductive healthcare. As AI-based technologies continue to evolve, their integration into reproductive medicine is expected to pave the way for more accessible, cost-effective, and personalized fertility care. |
