Artificial Intelligence in Obstetrics and Gynecology: Current Applications and Future Prospects

Abstract

Artificial intelligence is moving from demonstration projects to clinically relevant tools across obstetrics and gynecology. The specialty is especially well suited to algorithmic support because it combines image-heavy workflows, longitudinal electronic records, time-series monitoring, pathology, operative video, and urgent decisions that are often made under uncertainty. This review synthesizes current applications of artificial intelligence in fetal ultrasound, pregnancy risk prediction, intrapartum monitoring, cervical cancer screening, gynecologic oncology, benign gynecologic imaging, assisted reproductive technology, and large language model-enabled education and communication. Recent evidence indicates that the most mature use cases are image-based and tightly bounded tasks such as gestational-age estimation from ultrasound sweeps, cytology triage, and structured embryo assessment. Risk-prediction models for preeclampsia, postpartum hemorrhage, and fetal acidemia are increasingly sophisticated, but their translational value depends less on headline area-under-the-curve results than on calibration, external validation, workflow integration, and the quality of the actions triggered by the prediction. In gynecology, artificial intelligence is strengthening screening and subspecialty diagnostics rather than replacing expert judgment. In reproductive medicine, algorithmic embryo scoring is approaching routine adjunctive use, yet outcome prediction remains constrained by the fact that implantation and live birth depend on much more than embryo morphology alone. Across domains, the central implementation barriers are dataset shift, limited representativeness, labeling quality, automation bias, regulatory uncertainty, and uneven digital infrastructure. The near future of artificial intelligence in obstetrics and gynecology will likely be defined by multimodal models, human-centered interfaces, prospective impact trials, privacy-preserving multicenter collaboration, and equity-focused development. The strongest conclusion from the current literature is that artificial intelligence is most valuable when it functions as a carefully monitored clinical partner rather than an autonomous substitute for obstetric and gynecologic expertise.

Central Medical College Journal Vol 9 No 2 July 2025 Page: 111-124