ArticleFrontiers in dementia2026
Artificial intelligence in dementia care: challenges, controversies, and policy implications.
Article in Frontiers in dementia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly expanding into dementia-related health and social care, with proposed applications ranging from early risk detection and monitoring to care coordination and service planning. While these technologies may support independence, reduce caregiver burden, and improve efficiency in overstretched systems, dementia care is a uniquely high-stakes context for digital innovation. Cognitive decline can affect consent and agency, care often occurs in private domestic settings, and individuals may become increasingly dependent on others to interpret and act on algorithmic outputs. This Perspective examines the opportunities and challenges of AI in dementia policies and services, focusing on equity, privacy, accountability, and the risk that technologies displace human care. We argue that AI tools are only as reliable and fair as the data and infrastructures on which they depend, and that uneven access to digital resources may widen disparities in diagnosis, monitoring, and support. We also highlight often-overlooked considerations, including environmental sustainability and the broader role of AI in shaping exposures relevant to brain health across the life course. Whether AI improves dementia care will ultimately depend on policy and governance choices, including investment in equitable digital infrastructure, robust real-world validation, and safeguards that prevent technology from substituting for human care. Finally, we propose governance priorities to ensure that AI-enabled dementia innovations are implemented as a public-interest matter, grounded in meaningful engagement of people living with dementia and care partners, real-world validation, and safeguards that protect dignity, autonomy, and social legitimacy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.