Abstract
BackgroundArtificial intelligence (AI) mimics the way the human brain processes information. Machine learning (ML) is a subarea of AI that can be used to extract knowledge from large amounts of data, whereby different ML methods can be differentiated. The use of AI can help obstetricians to make informed decisions, reduce the number of medical errors and improve the accuracy in interpreting various diagnoses.ObjectiveIn the field of obstetrics, studies that describe the successful use of ML in screening for risks in pregnancy and the prediction of an adverse perinatal outcome (APO) are increasing. The following overview examines the potential of AI-supported obstetric monitoring with a focus on the most common problem areas in perinatal medicine. With their help, under certain circumstances an objective analysis of real data with the aim of identifying the most important risk factors and ultimately reducing the rate of APO can be made possible.
Published Version
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