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Community Detection Algorithms in Healthcare Applications: A Systematic Review

Authors :
Mehrdad Rostami
Mourad Oussalah
Kamal Berahmand
Vahid Farrahi
Source :
IEEE Access, Vol 11, Pp 30247-30272 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

Over the past few years, the number and volume of data sources in healthcare databases has grown exponentially. Analyzing these voluminous medical data is both opportunity and challenge for knowledge discovery in health informatics. In the last decade, social network analysis techniques and community detection algorithms are being used more and more in scientific fields, including healthcare and medicine. While community detection algorithms have been widely used for social network analysis, a comprehensive review of its applications for healthcare in a way to benefit both health practitioners and the health informatics community is still overwhelmingly missing. This paper contributes to fill in this gap and provide a comprehensive and up-to-date literature research. Especially, categorizations of existing community detection algorithms are presented and discussed. Moreover, most applications of social network analysis and community detection algorithms in healthcare are reviewed and categorized. Finally, publicly available healthcare datasets, key challenges, and knowledge gaps in the field are studied and reviewed.

Details

Language :
English
ISSN :
21693536
Volume :
11
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.56169625936d43409f0813436fc9aa0f
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2023.3260652