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

被引:1
|
作者
Liu, Xiangyu [1 ,2 ]
Zhang, Yingying [1 ,2 ]
Zhu, Haogang [2 ,3 ,4 ]
Jia, Bosen [5 ]
Wang, Jingyi [6 ,7 ]
He, Yihua [6 ,7 ]
Zhang, Hongjia [2 ,8 ]
机构
[1] Beihang Univ, Sch Biol Sci & Med Engn, Beijing, Peoples R China
[2] Beihang Univ, Int Innovat Inst, Key Lab Data Sci & Intelligent Comp, Hangzhou 311115, Peoples R China
[3] Beihang Univ, State Key Lab Software Dev Environm, Beijing, Peoples R China
[4] Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China
[5] Victoria Univ Wellington, Sch Biol Sci, Wellington, New Zealand
[6] Capital Med Univ, Echocardiog Med Ctr, Beijing Anzhen Hosp, Beijing, Peoples R China
[7] Beijing Anzhen Hosp, Maternal Fetal Med Ctr Fetal Heart Dis, Beijing, Peoples R China
[8] Beijing Lab Cardiovasc Precis Med, Beijing, Peoples R China
来源
关键词
congenital heart disease; artificial intelligence; prenatal diagnosis; fetal echocardiography; deep learning; CHROMOSOMAL-ABNORMALITIES; MOTION CORRECTION; NEURAL-NETWORK; UNITED-STATES; RISK-FACTORS; DEFECTS; SEGMENTATION; ULTRASOUND; MRI; LOCALIZATION;
D O I
10.3389/fcvm.2024.1345761
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Artificial Intelligence for the Prenatal Ultrasound Diagnosis of Congenital Heart Disease: A Narrative Review
    Riva, Arianna
    Guerra, Mariachiara
    Di Gangi, Stefania
    Veronese, Paola
    Vida, Vladimiro L.
    CLINICAL AND EXPERIMENTAL OBSTETRICS & GYNECOLOGY, 2024, 51 (11):
  • [2] Artificial Intelligence-Powered Materials Science
    Bai, Xiaopeng
    Zhang, Xingcai
    NANO-MICRO LETTERS, 2025, 17 (01)
  • [3] Artificial intelligence-powered electronic skin
    Xu, Changhao
    Solomon, Samuel A.
    Gao, Wei
    NATURE MACHINE INTELLIGENCE, 2023, 5 (11) : 1344 - 1355
  • [4] Artificial intelligence-powered electronic skin
    Changhao Xu
    Samuel A. Solomon
    Wei Gao
    Nature Machine Intelligence, 2023, 5 : 1344 - 1355
  • [5] Artificial Intelligence-Powered Materials Science
    Xiaopeng Bai
    Xingcai Zhang
    Nano-Micro Letters, 2025, 17 (06) : 220 - 249
  • [6] Artificial intelligence-powered precision: Unveiling the landscape of liver disease diagnosis-A comprehensive review
    Vadlamudi, Sireesha
    Kumar, Vimal
    Ghosh, Debjani
    Abraham, Ajith
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2024, 138
  • [7] Editorial: Artificial Intelligence-Powered Methodologies and Applications in Earthquake and Structural Engineering
    Lu, Xinzheng
    Plevris, Vagelis
    Tsiatas, George
    De Domenico, Dario
    FRONTIERS IN BUILT ENVIRONMENT, 2022, 8
  • [8] Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease
    de Vries, Ivar R. R.
    van Laar, Judith O. E. H.
    van der Hout-van der Jagt, Marieke B.
    Clur, Sally-Ann B.
    Vullings, Rik
    ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA, 2023, 102 (11) : 1511 - 1520
  • [9] Artificial Intelligence-Powered Blockchains for Cardiovascular Medicine
    Krittanawong, Chayakrit
    Aydar, Mehmet
    Virk, Hafeez Ul Hassan
    Kumar, Anirudh
    Kaplin, Scott
    Guimaraes, Lucca
    Wang, Zhen
    Halperin, Jonathan L.
    CANADIAN JOURNAL OF CARDIOLOGY, 2022, 38 (02) : 185 - 195
  • [10] The Seductive Allure of Artificial Intelligence-Powered Neurotechnology
    Giattino, Charles M.
    Kwong, Lydia
    Rafetto, Chad
    Farahany, Nita A.
    AIES '19: PROCEEDINGS OF THE 2019 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY, 2019, : 397 - 402