Evolution, hotspots, and prospects of AI-powered telehealth: A bibliometric study

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.