Abstract Objective Artificial intelligence (AI) applications have garnered increasing interest in obstetrics and gynecology. This study aims to analyze the evolving research themes, temporal trends, and conceptual frameworks of AI applications in this field through a comprehensive bibliometric analysis. Methods A total of 815 original research articles published between 1980 and 2025 were retrieved from the Web of Science Core Collection using keywords such as “artificial intelligence,” “machine learning,” and “deep learning” within obstetrics and gynecology. Trend keyword analysis and factor analysis were conducted using the Bibliometrix package in R Studio to identify thematic clusters and research trajectories. Results The USA ( n = 194), China ( n = 168), and Japan ( n = 44) were the most prolific countries, with Harvard University as the leading institution ( n = 68). Key research focuses included in vitro fertilization, breast cancer, pregnancy complications (e.g., preeclampsia, gestational diabetes mellitus), assisted reproductive technology, cervical cancer, embryo selection, and patient education. Since 2020, research emphasis has shifted toward fertility, oncological gynecology, pregnancy complications, and patient education, with notable growth in topics such as preeclampsia and breast cancer during 2023–2024. Factor analysis revealed six thematic clusters encompassing clinical decision support systems, reproductive technologies, oncological modeling, and perinatal risk analysis. Conclusion AI is increasingly affecting obstetrics and gynecology beyond diagnostics and treatment, extending to risk prediction, patient education, and personalized medicine. Despite its transformative potential, challenges such as algorithmic bias, data security, and ethical considerations warrant vigilant attention.
Seniye Burcu Torumtay Aliç (2026) studied this question.