Authors
Bingnan Du, Qi Li, Xueying Li, Xiaoxi Liu, Ke Zhang, Yifan Gong, Jiangdian Song, Hui Wu
Published in
The Gerontologist. Jun 15, 2026. Epub Jun 15, 2026.
Abstract
Population aging and the rising prevalence of Alzheimer's Disease and Related Dementias (AD/ADRD) have created an urgent need for innovative care solutions. Artificial Intelligence (AI) has emerged as a critical tool, yet a macro-level quantitative analysis of its evolutionary trajectory in geriatric care remains scarce. This study conducts a comprehensive bibliometric analysis to map the knowledge domain of AI-empowered geriatric care for AD/ADRD from 2004 to 2025, elucidating spatial distributions, evolutionary trajectories, and emerging research frontiers.
A total of 1,197 eligible records were retrieved from the Web of Science Core Collection (WoSCC). Bibliometric analyses including co-occurrence networks, burst detection, and thematic evolution were conducted utilizing CiteSpace, VOSviewer, and the Bibliometrix R package.
The 1,197 documents (402 sources; 7,268 authors) show an annual growth rate of 30.36%, peaking at 262 publications in 2025. The United States (242 articles; 6,640 citations) and China (213 articles; 3,649 citations) dominate global output, with Harvard University and the University of London as primary hubs, though the Global South remains underrepresented. Thematic evolution reveals three phases: early "smart homes" and "activity detection"; middle "home monitoring" and "social robots"; and a current frontier of "explainable AI" and biomarker-driven risk assessment. Keyword bursts confirm "tau" and "intervention" as leading hotspots to 2025.
AI in AD/ADRD care is transitioning from environmental assistance to neuro-precision diagnostics and therapeutics. Future research should integrate ethical, multimodal AI to bridge care gaps and facilitate high-quality aging-in-place.
PMID:
42295865
Bibliographic data and abstract were imported from PubMed on 15 Jun 2026.
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