Artificial intelligence in obstetrics and gynecology: Transforming care and outcomes

Abstract

Artificial intelligence (AI) has increasingly become a transformative force in healthcare, with obstetrics and gynecology (OB/GYN) being a key area of impact. In prenatal diagnostics, AI algorithms assist in analyzing ultrasound images, fetal echocardiography, and genetic screening, enabling earlier and more accurate detection of congenital anomalies. During labor and delivery, AI-powered monitoring systems can track maternal and fetal vital signs in real time, predict complications such as fetal distress, and support timely clinical interventions. In reproductive endocrinology, AI enhances assisted reproductive technologies by optimizing embryo selection, predicting IVF success rates, and personalizing hormone therapy regimens. Gynecologic oncology benefits from AI applications in early cancer detection, histopathological analysis, and treatment planning, improving survival outcomes and reducing diagnostic errors. Furthermore, AI aids in patient risk stratification by integrating electronic health records, laboratory data, and imaging studies to identify high-risk pregnancies and guide preventive strategies. Despite these advancements, challenges remain, including data privacy concerns, algorithmic bias, the need for large annotated datasets, and integration into clinical workflows without disrupting care. Ethical considerations, such as informed consent, transparency, and accountability for AI-driven decisions, are critical to ensure patient trust and equitable healthcare delivery. Future directions in OB/GYN emphasize combining AI with wearable health monitoring, telemedicine, and predictive analytics to enable continuous, personalized, and proactive care. This review synthesizes evidence from the past decade, highlighting AI’s potential to enhance clinical decision-making, reduce errors, and improve maternal and fetal outcomes

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