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=Volume 9 - 2022

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) has been around for over 100 years and is considered the gold standard for blood pressure (BP) measurement. K-sounds is also unique for diagnosis and treatment of cardiovascular diseases, however, its efficacy is limited. Heart failure (HF) incidences are increasing, which necessitates 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 detection of cardiac dysfunctions.