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Applications of artificial intelligence-powered prenatal diagnosis for congenital heart disease

Authors :
Xiangyu Liu
Yingying Zhang
Haogang Zhu
Bosen Jia
Jingyi Wang
Yihua He
Hongjia Zhang
Source :
Frontiers in Cardiovascular Medicine, Vol 11 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

Artificial intelligence (AI) has made significant progress in the medical field in the last decade. The AI-powered analysis methods of medical images and clinical records can now match the abilities of clinical physicians. Due to the challenges posed by the unique group of fetuses and the dynamic organ of the heart, research into the application of AI in the prenatal diagnosis of congenital heart disease (CHD) is particularly active. In this review, we discuss the clinical questions and research methods involved in using AI to address prenatal diagnosis of CHD, including imaging, genetic diagnosis, and risk prediction. Representative examples are provided for each method discussed. Finally, we discuss the current limitations of AI in prenatal diagnosis of CHD, namely Volatility, Insufficiency and Independence (VII), and propose possible solutions.

Details

Language :
English
ISSN :
2297055X
Volume :
11
Database :
Directory of Open Access Journals
Journal :
Frontiers in Cardiovascular Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.5f6802e270684743abdceabfc8338a88
Document Type :
article
Full Text :
https://doi.org/10.3389/fcvm.2024.1345761