Korotkoff sounds dynamically reflect changes in cardiac function based on deep learning methods

Wenting Lin; Sixiang Jia; Yiwen Chen; Hanning Shi; Jianqiang Zhao; Zhe Li; Yiteng Wu; Hangpan Jiang; Qi Zhang; Wei Wang; Yayu Chen; Chao Feng; Shudong Xia

doi:10.3389/fcvm.2022.940615

Korotkoff sounds dynamically reflect changes in cardiac function based on deep learning methods

Front Cardiovasc Med. 2022 Aug 26:9:940615. doi: 10.3389/fcvm.2022.940615. eCollection 2022.

Authors

Wenting Lin¹, Sixiang Jia¹, Yiwen Chen¹, Hanning Shi², Jianqiang Zhao¹, Zhe Li¹, Yiteng Wu¹, Hangpan Jiang¹, Qi Zhang¹, Wei Wang¹, Yayu Chen¹, Chao Feng¹, Shudong Xia¹

Affiliations

¹ Department of Cardiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China.
² Department of Anime and Comics, Hangzhou Normal University, Hangzhou, China.

Abstract

Korotkoff sounds (K-sounds) have been around for over 100 years and are considered the gold standard for blood pressure (BP) measurement. K-sounds are also unique for the diagnosis and treatment of cardiovascular diseases; however, their efficacy is limited. The incidences of heart failure (HF) are increasing, which necessitate the development of a rapid and convenient pre-hospital screening method. In this review, we propose a deep learning (DL) method and the possibility of using K-methods to predict cardiac function changes for the detection of cardiac dysfunctions.

Keywords: Korotkoff sounds; cardiac function; deep learning; heart failure; prediction.

Publication types

Review