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    REVIEW

    Machine Learning-Based Intelligent Auscultation Techniques in Congenital Heart Disease: Application and Development

    Yang Wang#, Xun Yang#, Mingtang Ye, Yuhang Zhao, Runsen Chen, Min Da, Zhiqi Wang, Xuming Mo, Jirong Qi*

    Congenital Heart Disease, Vol.19, No.2, pp. 219-231, 2024, DOI:10.32604/chd.2024.048314

    Abstract Congenital heart disease (CHD), the most prevalent congenital ailment, has seen advancements in the “dual indicator” screening program. This facilitates the early-stage diagnosis and treatment of children with CHD, subsequently enhancing their survival rates. While cardiac auscultation offers an objective reflection of cardiac abnormalities and function, its evaluation is significantly influenced by personal experience and external factors, rendering it susceptible to misdiagnosis and omission. In recent years, continuous progress in artificial intelligence (AI) has enabled the digital acquisition, storage, and analysis of heart sound signals, paving the way for intelligent CHD auscultation-assisted diagnostic technology. Although More > Graphic Abstract

    Machine Learning-Based Intelligent Auscultation Techniques in Congenital Heart Disease: Application and Development

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