Artificial intelligence, fetal echocardiography, and congenital heart disease
Author(s)
Day, Thomas G
Kainz, Bernhard
Hajnal, Jo
Razavi, Reza
Simpson, John M
Type
Journal Article
Abstract
There has been a recent explosion in the use of artificial intelligence (AI), which is now part of our everyday lives. Uptake in medicine has been more limited, although in several fields there have been encouraging results showing excellent performance when AI is used to assist in a well-defined medical task. Most of this work has been performed using retrospective data, and there have been few clinical trials published using prospective data. This review focuses on the potential uses of AI in the field of fetal cardiology. Ultrasound of the fetal heart is highly specific and sensitive in experienced hands, but despite this there is significant room for improvement in the rates of prenatal diagnosis of congenital heart disease in most countries. AI may be one way of improving this. Other potential applications in fetal cardiology include the provision of more accurate prognoses for individuals, and automatic quantification of various metrics including cardiac function. However, there are also ethical and governance concerns. These will need to be overcome before AI can be widely accepted in mainstream use. It is likely that a familiarity of the uses, and pitfalls, of AI will soon be mandatory for many healthcare professionals working in fetal cardiology.
Date Issued
2021-05-01
Date Acceptance
2020-12-25
Citation
Prenatal Diagnosis, 2021, 41 (6)
ISSN
0197-3851
Publisher
Wiley
Journal / Book Title
Prenatal Diagnosis
Volume
41
Issue
6
Copyright Statement
© 2021 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000615094700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Life Sciences & Biomedicine
Genetics & Heredity
Obstetrics & Gynecology
Publication Status
Published
Date Publish Online
2021-01-18