Artificial intelligence based on falling in older people: A bibliometric analysis

Abstract Objectives This study aimed to analyze publications on artificial intelligence (AI) for falls in older people from a bibliometric perspective. Methods The Web of Science database was searched for titles of English‐language articles containing the words “artificial intelligence,” “deep learning,” “machine learning,” “natural language processing,”, “neural artificial network,” “fall,” “geriatric,” “elderly,” “aging,” “older,” and “old age.” An R‐based application (Biblioshiny for bibliometrics) and VOSviewer software were used for analysis. Results Thirty‐seven English articles published between 2018 and 2024 were included. The year 2023 is the year with the most publications with 16 articles. The most productive research field was “Engineering Electrical Electronic” with seven articles. The most productive country was the United States, followed by China. The most common words were “injuries,” “people,” and “risk factors.” Conclusion Publications on AI and falls in the elderly are both few in number and the number of publications has increased in recent years. Future research should include relevant analyses in scientific databases, such as Scopus and PubMed.