Benefits of AI-assisted obstetric surveillance

被引:0
|
作者
Graupner, O. [1 ,2 ]
Enzensberger, C. [1 ]
机构
[1] Univ Klinikum Aachen, RWTH Aachen, Klin Gynakol & Geburtsmed, Pauwelsstr 30, D-52074 Aachen, Germany
[2] Tech Univ Munich, Univ Klinikum Rechts Isar, Frauenklin & Poliklin, Munich, Germany
来源
GYNAKOLOGIE | 2022年 / 55卷 / 10期
关键词
Machine learning; Artificial intelligence; Obstetrics; Fetal monitoring; Decision making; ARTIFICIAL-INTELLIGENCE; GESTATIONAL-AGE; CLASSIFICATION; CARDIOTOCOGRAPHY; PREDICTIONS;
D O I
10.1007/s00129-022-04994-7
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
Background Artificial 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. Objective In 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.
引用
收藏
页码:740 / 745
页数:6
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