Artificial intelligence technology in cardiac auscultation screening for congenital heart disease: present and future

doi:10.3785/j.issn.1008-9292.2020.10.01

J Zhejiang Univ (Med Sci)

2020, Vol. 49

Issue (5): 548-555 DOI: 10.3785/j.issn.1008-9292.2020.10.01

Artificial intelligence technology in cardiac auscultation screening for congenital heart disease: present and future

XU Weize(

),YU Kai,XU Jiajun,YE Jingjing,LI Haomin,SHU Qiang*(

)

The Heart Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Regional Medical Center for Children, Hangzhou 310052, China

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Abstract

The electronic stethoscope combined with artificial intelligence (AI) technology has realized the digital acquisition of heart sounds and intelligent identification of congenital heart disease, which provides objective basis for heart sound auscultation and improves the accuracy of congenital heart disease diagnosis. At the present stage, the AI based cardiac auscultation technique mainly focuses on the research of AI algorithms, and the researchers have designed and summarized a variety of effective algorithms based on the characteristics of cardiac audio data, among which the mel-frequency cepstral coefficients (MFCC) is the most effective one, and widely used in the cardiac auscultation. However, the current cardiac sound analysis techniques are based on specific data sets, and have not been validated in clinic, so the performance of algorithms need to be further verified. The lack of heart sound data, especially the high-quality, standardized, publicly available heart sound database with disease labeling, further restricts the development of heart sound diagnostic analysis and its application in screening. Therefore, expert consensus is necessary in establishing an authoritative heart sound database and standardizing the heart sound auscultation screening process for congenital heart disease. This paper provides an overview of the research and application status of auscultation algorithm and hardware equipment based on AI in auscultation screening of congenital heart disease, and puts forward the problems to be solved in clinical application of AI auscultation screening technology.

Key words： Heart defects, congenital Neonatal screening Heart auscultation Artificial intelligence

Received: 27 August 2020 Published: 19 November 2020

CLC:

R44

Corresponding Authors: SHU Qiang E-mail: 120heart@zju.edu.cn;shuqiang@zju.edu.cn

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	XU Weize
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	LI Haomin
	SHU Qiang

Cite this article:

XU Weize,YU Kai,XU Jiajun,YE Jingjing,LI Haomin,SHU Qiang. Artificial intelligence technology in cardiac auscultation screening for congenital heart disease: present and future. J Zhejiang Univ (Med Sci), 2020, 49(5): 548-555.

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http://www.zjujournals.com/med/10.3785/j.issn.1008-9292.2020.10.01 OR http://www.zjujournals.com/med/Y2020/V49/I5/548

先天性心脏病心音听诊筛查的人工智能技术应用现状

近年来，电子听诊器结合人工智能技术实现了心音的数字化采集和先天性心脏病的智能识别，为心音听诊提供了客观依据，提高了先天性心脏病诊断的准确率。现阶段基于人工智能技术的智能听诊技术主要侧重于人工智能算法的研究，国内外学者也针对心音音频数据的特点设计总结了多种有效算法，其中梅尔频率倒谱系数（MFCC）是最常用且有效的心音特征，被广泛应用于智能听诊技术中。然而，当前心音智能听诊技术均基于筛选的特定数据集实现，并且尚未在实际临床环境中基于大样本进行实验验证，因此各个算法的实际临床应用表现尚待进一步验证。心音数据匮乏，特别是高质量、标准化、带疾病标注且公开的心音数据库的缺失，进一步制约了心音智能诊断分析技术的发展和听诊筛查的应用。因此，相关医疗单位应当组织有关专家共同建立先天性心脏病心音听诊筛查的专家共识和标准化心音听诊筛查流程，并以此建立权威心音数据库。本文就现阶段基于人工智能的听诊算法和硬件设备在先天性心脏病听诊筛查中的研究及应用进行综述，提出人工智能心音听诊筛查技术在临床应用中有待解决的问题。

关键词： 心脏缺损, 先天性, 新生儿筛查, 心脏听诊, 人工智能

Fig 1 Diagram of heart sound waveform^[4]

Fig 2 The principal processes of artificial intelligence-based heart sound auscultation

Tab 1 An introduction to the function, advantages and disadvantages of electronic stethoscope equipment and systems


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