Editorial: Diagnosis, monitoring, and treatment of heart rhythm: new insights and novel computational methods

Jieyun Bai; Jichao Zhao; Haibo Ni; Dechun Yin

doi:10.3389/fphys.2023.1272377

Editorial: Diagnosis, monitoring, and treatment of heart rhythm: new insights and novel computational methods

Front Physiol. 2023 Aug 16:14:1272377. doi: 10.3389/fphys.2023.1272377. eCollection 2023.

Authors

Jieyun Bai^{1

2}, Jichao Zhao², Haibo Ni³, Dechun Yin⁴

Affiliations

¹ Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou, China.
² Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
³ Department of Pharmacology, University of California Davis, Davis, CA, United States.
⁴ Department of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.

No abstract available

Keywords: ECG; artificial intelligence; cardiac arrhythmias; computational modelling; deep learning; digital twin.

Publication types

Editorial

Grants and funding

The author declare financial support was received for the research, authorship, and/or publication of this article. Sources of support are the Guangdong Basic and Applied Basic Research Foundation (2023A1515012833), the Science and Technology Program of Guangzhou (202201010544), the National Natural Science Foundation of China (No. 61901192), the China Scholarship Council, and an American Heart Association Postdoctoral Fellowship 20POST35120462 (HN).