Newby, Danielle;
Orgeta, Vasiliki;
Marshall, Charles R;
Lourida, Ilianna;
Albertyn, Christopher P;
Tamburin, Stefano;
Raymont, Vanessa;
... TheDeepDementiaPhenotyping(DEMON)Network, .; + view all
(2023)
Artificial intelligence for dementia prevention.
Alzheimer's & Dementia
10.1002/alz.13463.
(In press).
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Abstract
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.
Type: | Article |
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Title: | Artificial intelligence for dementia prevention |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1002/alz.13463 |
Publisher version: | https://doi.org/10.1002/alz.13463 |
Language: | English |
Additional information: | © 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | artificial intelligence, dementia, machine learning, prevention, risk prediction. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry > Mental Health of Older People |
URI: | https://discovery.ucl.ac.uk/id/eprint/10179002 |
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