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Artificial Intelligence in Obstetrics
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AI
DOI：10.1097/GRF.0000000000000980.png)
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Abstract
En 中文
Artificial intelligence is transforming obstetric practice through applications in diagnostic imaging, risk prediction, and clinical decision-making. Deep learning algorithms have achieved diagnostic accuracy comparable to that of experienced clinicians. However, gaps persist between algorithmic capability and clinical implementation. Critical challenges include limited external validation and algorithmic bias. This review examines current AI applications in obstetrics across multiple clinical domains: automated fetal biometry, structural anomaly detection, prediction of pregnancy complications, and intrapartum fetal surveillance. It highlights persistent technical, ethical, and implementation barriers. Key recommendations include multicenter validation across diverse populations, explainable AI approaches, and creating strong regulatory frameworks.
Keywords:
artificial intelligence
machine learning
deep learning
fetal biometry
anomaly detection
preeclampsia prediction
Journal
C
IF:
1.4
Papers:
31
Citations:
0