Evaluating the Role of Artificial Intelligence in Fetal Medicine: Opportunities, Evidence, and Challenges, A Narrative Review

Abstract

Artificial intelligence has emerged as a promising tool in fetal medicine, with applications in prenatal imaging, anomaly detection, and biometric analysis. Peer-reviewed studies have reported high accuracy for AI models in identifying congenital heart defects, segmenting brain structures, and predicting fetal growth patterns. Despite strong retrospective performance, most tools remain investigational due to limited external validation, lack of explainability, and poor integration with clinical workflows. This review synthesizes current evidence on AI applications in fetal diagnostics, highlights both capabilities and limitations, and outlines future directions needed for safe and effective clinical translation.

Keywords: artificial intelligence; congenital anomalies; deep learning; fetal imaging; prenatal diagnosis; ultrasound.