Artificial intelligence applications and aging (1995-2024): Trends, challenges, and future directions in frailty...

Frailty, a significant predictor of adverse health outcomes, has become a focal point of research, particularly with the advent of artificial intelligence (AI) technologies. This study aimed to provide a comprehensive bibliometric analysis of research trends in AI and frailty to map conceptual developments, collaborations, and emerging themes in the field.

A systematic search was conducted using the Scopus database employing a comprehensive set of keywords related to AI and frailty. The search was refined to include only original articles in English, yielding 1213 documents. Data extraction was performed in October 2024 and exported in the CSV and BibTeX formats. Annual growth trends were analyzed using Microsoft Excel, while VOSviewer and R-package were used for bibliometric analyzes and visualization to identify key contributors, collaborations, and thematic clusters.

The analysis revealed rapid growth in research publications, with AI applications in frailty gaining prominence over the past decade. Thematic clusters highlight areas such as predictive modeling, machine learning applications, and geriatric care innovations. The United States, United Kingdom, and Italy emerged as leading contributors to publications and collaborations. The key topics included prediction models, dementia, sarcopenia, and rehabilitation. This bibliometric study underscores the increasing integration of AI into frailty research, revealing key trends, collaborative networks, and emerging areas of focus.

These findings can guide future research, foster collaborations, and enhance the application of AI technologies to improve frailty assessment and management.