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
Department of Cardiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China.
Department of Anime and Comics, Hangzhou Normal University, Hangzhou, China.
Front Cardiovasc Med. 2022 Aug 26;9:940615. doi: 10.3389/fcvm.2022.940615. eCollection 2022.
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.
柯氏音（K音）已经存在了100多年，被认为是血压（BP）测量的金标准。K音在心血管疾病的诊断和治疗中也具有独特性；然而，其功效有限。心力衰竭（HF）的发病率正在上升，这就需要开发一种快速便捷的院前筛查方法。在本综述中，我们提出一种深度学习（DL）方法以及使用K音方法预测心功能变化以检测心脏功能障碍的可能性。
