A Comprehensive Bibliometric Analysis of Pulmonary Rehabilitation: Focus on the Top 100 Most-cited Papers and Involvement of Artificial Intelligence
Monira I. Aldhahi, Siddig Ibrahim Abdelwahab, Manal Mohamed Elhassan Taha, Ali Albarrati, Umut Canli, Waseem HassanAbstract
Background:
This study aimed to perform a bibliometric analysis of pulmonary rehabilitation (PR) research to map global trends, identify key contributors, and pinpoint knowledge gaps. Understanding the trajectory of PR research can guide strategies to improve patient outcomes and shape future investigations.
Materials and Methods:
Data were retrieved from Scopus (2001-2023) using a systematic search strategy. Three analytical approaches were employed: (1) overall publication trends, (2) analysis of the top 100 most-cited papers, and (3) exploration of the intersection between PR, artificial intelligence (AI), and machine learning. Bibliometric tools such as VOSviewer and R Studio (bibliometrix/biblioshiny) were utilized for analysis.
Results:
The analysis identified 5,808 publications, including 4,287 articles and 1,521 reviews. Europe led with 3,003 publications, followed by Asia (931), whereas contributions from South America and the Middle East were limited (e.g., Brazil: 273; Saudi Arabia: 57). African countries produced fewer than 50 papers, highlighting global disparities in research. Key authors, institutions, and sponsors were identified, with bibliometric metrics (h-index and g-index) quantifying influence. Only 33 publications addressed the integration of AI and PR, revealing a significant knowledge gap.
Conclusions:
This study highlights a robust PR research body with limited integration of AI and significant regional disparities. Promoting equitable research efforts and advancing AI applications could enhance PR and patient care.