AUTHOR=Yang Mengting , Zhang Hongchao , Liu Weichao , Yong Kangle , Xu Jie , Luo Yamei , Zhang Henggui 

TITLE=Knowledge graph analysis and visualization of artificial intelligence applied in electrocardiogram

JOURNAL=Frontiers in Physiology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2023.1118360

DOI=10.3389/fphys.2023.1118360

ISSN=1664-042X

ABSTRACT=Background: 
Electrocardiogram (ECG) provides a straightforward and non-invasive approach for various applications, such as disease classification, biometric identification, emotion recognition, and so on. In recent years, artificial intelligence (AI) shows excellent performance and plays an increasingly important role in ECG research as well.
Objective: 
This study mainly adopts the literature on the applications of AI in ECG research to focus on the development process through bibliometric and visual knowledge graph methods.
Methods: 
The 2229 publications collected from the Web of Science Core Collection (WoSCC) database until 2021 are employed as the research objects, and a comprehensive metrology and visualization analysis based on CiteSpace (version 6.1.R3) and VOSviewer (version 1.6.18) platform, which were conducted to explore the co-authorship, co-occurrence and co-citation of countries/regions, institutions, authors, journals, categories, references and keywords regarding AI applied in ECG. 
Results: 
In the recent four years, both the annual publications and citations of AI in ECG sharply increased. China published the most articles while Singapore had the highest ACP (average citations per article). The most productive institution and authors were Ngee Ann Polytech from Singapore and Acharya U. Rajendra from the University of Technology Sydney. The journal Computers in Biology and Medicine published the most influential publications, and the subject with the most published articles are distributed in Engineering Electrical Electronic. The evolution of research hotspots was analyzed by co-citation references' cluster knowledge visualization domain map. In addition, deep learning, attention mechanism, data augmentation, and so on were the focuses of recent research through the co-occurrence of keywords.