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

dc.contributor.authorYenisehir, Semiha
dc.date.accessioned2024-12-14T22:07:14Z
dc.date.available2024-12-14T22:07:14Z
dc.date.issued2024
dc.departmentMuş Alparslan Üniversitesien_US
dc.description.abstractObjectivesThis study aimed to analyze publications on artificial intelligence (AI) for falls in older people from a bibliometric perspective.MethodsThe 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.ResultsThirty-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.ConclusionPublications 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. The English-articles based on artificial intelligence and falls in the older people are both few in number. The number of publications has increased in recent years according to technological developments. In future research, relevant analyzes should be conducted in scientific databases, such as Scopus and PubMed.imageen_US
dc.identifier.doi10.1002/agm2.12302
dc.identifier.endpage170en_US
dc.identifier.issn2475-0360
dc.identifier.issue2en_US
dc.identifier.orcid0000-0002-3928-2207
dc.identifier.pmid38725694
dc.identifier.scopus2-s2.0-85190459628
dc.identifier.scopusqualityQ3
dc.identifier.startpage162en_US
dc.identifier.urihttps://doi.org/10.1002/agm2.12302
dc.identifier.urihttps://hdl.handle.net/20.500.12639/6457
dc.identifier.volume7en_US
dc.identifier.wosWOS:001199061500001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherWileyen_US
dc.relation.ispartofAging Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzKA_20241214
dc.subjectartificial intelligence (AI)en_US
dc.subjectfallingen_US
dc.subjectgeriatricsen_US
dc.subjectolder adultsen_US
dc.subjectweb of science (WoS)en_US
dc.titleArtificial intelligence based on falling in older people: A bibliometric analysisen_US
dc.typeArticle

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