Artificial intelligence for dementia prevention
INTRODUCTION A 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 i...
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Veröffentlicht in: | Alzheimer's & dementia 2023-12, Vol.19 (12), p.5952-5969 |
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Hauptverfasser: | , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | INTRODUCTION
A 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.
METHODS
ML approaches are being developed in dementia prevention. We discuss exemplar uses and evaluate the current applications and limitations in the dementia prevention field.
RESULTS
Risk‐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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ISSN: | 1552-5260 1552-5279 1552-5279 |
DOI: | 10.1002/alz.13463 |