Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Applied Computer and Information Technology
Nur Suhaili Mansor
Institute for Advanced and Smart Digital Opportunities, School of Computing, Universiti Utara Malaysia, Malaysia

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Evolution, hotspots, and prospects of AI-powered telehealth: A bibliometric study Bingxin Jin; Hapini Awang; Nur Suhaili Mansor
Journal of Applied Computer and Information Technology Vol. 1 No. 1 (2026): Journal of Applied Computer and Information Technology (JACoIT)
Publisher : Global Research Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67131/jacoit.v1i1.5

Abstract

The integration of artificial intelligence (AI) and telehealth has become a key enabler of smart healthcare, improving accessibility and efficiency in medical services. However, comprehensive reviews focusing on the evolution, knowledge structure, and future directions of AI-powered telehealth remain limited. This study addresses this gap by conducting a bibliometric analysis of 427 publications indexed in the Scopus database from 2010 to 2025. The analysis examines publication trends, citation patterns, influential studies, and keyword co-occurrence networks. The findings reveal a two-phase development pattern characterized by “scale expansion” followed by “quality improvement”, with 2020 identified as a critical turning point. The results further highlight three major clusters of influential research focusing on AI-based diagnosis, specialized healthcare applications, and technological integration. In addition, four primary research themes are identified: AI-based telehealth applications, enabling technologies, research methodologies, and precision telehealth. Emerging research directions include the development of mobile health solutions, explainable AI, mixed-method approaches, and improvements in system capacity and reliability. This study provides a comprehensive knowledge framework and offers theoretical and practical insights to support the sustainable and high-quality development of AI-powered telehealth.
Co-Authors Bingxin Jin Hapini Awang