AUTHOR=Lin Wenting , Jia Sixiang , Chen Yiwen , Shi Hanning , Zhao Jianqiang , Li Zhe , Wu Yiteng , Jiang Hangpan , Zhang Qi , Wang Wei , Chen Yayu , Feng Chao , Xia Shudong TITLE=Korotkoff sounds dynamically reflect changes in cardiac function based on deep learning methods JOURNAL=Frontiers in Cardiovascular Medicine VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2022.940615 DOI=10.3389/fcvm.2022.940615 ISSN=2297-055X 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.