ReviewAlzheimer's & dementia : the journal of the Alzheimer's Association2023
Artificial intelligence for dementia prevention.
Review in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical prediction models using artificial intelligence approaches in dementia.Aging clinical and experimental research · 2025Pooled it
- A strategic pathway for the ethical development of AI tools in dementia care.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Article
- Navigating the Artificial Intelligence Revolution in Clinical Neurology: A New Multidisciplinary Task Force Within the European Academy of Neurology.European journal of neurology · 2026Article
- Next generation preventive neurology: how artificial intelligence and machine learning are reshaping Alzheimer's disease research.Behavioral and brain functions : BBF · 2026Review
- Review
- Uncovering the role of integrated stress in Alzheimer's disease through single-cell and transcriptomic analysis.Scientific reports · 2026Article
- Article
- Multimodal neuroimaging and AI integration in cognitive disorders: advances, challenges, and future directions for precision medicine.Psychoradiology · 2026Review
- Evaluating the Role of AI Assistants in Accelerating Neurodegenerative Disease Research: Opportunities and Translational Limitations.Neuropsychiatric disease and treatment · 2026Review
- Broadening dementia risk models: building on the 2024 Lancet Commission report for a more inclusive global framework.EBioMedicine · 2025Review
- Personalized medication recommendations for Parkinson's disease patients using gated recurrent units and SHAP interpretability.Scientific reports · 2025Article
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Aptamer-functionalized graphene quantum dots combined with artificial intelligence detect bacteria for urinary tract infections.Frontiers in cellular and infection microbiology · 2025Article
- A Multivariable Prediction Model for Mild Cognitive Impairment and Dementia: Algorithm Development and Validation.JMIR medical informatics · 2024Article
- Beyond black-box AI: Interpretable hybrid systems for dementia care.Alzheimer's & dementia (Amsterdam, Netherlands)Review
- Artificial intelligence-based rapid brain volumetry substantially improves differential diagnosis in dementia.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Characteristics of publicly available digital dementia risk screening tools: A scoping review.Journal of Alzheimer's disease reportsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
introductionA wide range of modifiable risk factors for dementia have been identified. Considerable debate remains about these risk factors, possible interactions between them or with genetic risk, and causality, and how they can help in clinical trial recruitment and drug development. Artificial intelligence (AI) and machine learning (ML) may refine understanding.
methodsML approaches are being developed in dementia prevention. We discuss exemplar uses and evaluate the current applications and limitations in the dementia prevention field.
resultsRisk-profiling tools may help identify high-risk populations for clinical trials; however, their performance needs improvement. New risk-profiling and trial-recruitment tools underpinned by ML models may be effective in reducing costs and improving future trials. ML can inform drug-repurposing efforts and prioritization of disease-modifying therapeutics. DISCUSSION: ML is not yet widely used but has considerable potential to enhance precision in dementia prevention. HIGHLIGHTS: Artificial intelligence (AI) is not widely used in the dementia prevention field. Risk-profiling tools are not used in clinical practice. Causal insights are needed to understand risk factors over the lifespan. AI will help personalize risk-management tools for dementia prevention. AI could target specific patient groups that will benefit most for clinical trials.
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What OpenQuestion holds
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.