Artificial intelligence research ın women’s health: Bibliometric analysis of scientific publications between 2020–2025

Although AI applications in women's health are increasing rapidly, few bibliometric studies have systematically examined research trends and priority topics in this field. We conducted a bibliometric analysis of research on women's health and artificial intelligence published between 2020 and 2025 to interpret the field's evolution and identify gaps within it. We analyzed 3241 articles indexed in the Web of Science database, retrieved on 13.09.2025, using VOSviewer software and co--authorship, co-occurrence, citation, and country analysis techniques. We found that publications increased over the years, the USA produced the most, and the most-cited studies focused on obstetric imaging, gestational diabetes, and infertility. The most frequently used keywords were machine learning, pregnancy, artificial intelligence, deep learning, and fertility. Researchers in this field focus on clinically prioritized problems and use algorithm-based approaches. International collaboration and multidisciplinary approaches will accelerate its development.