Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
Division of Psychiatry, University College London, London, UK.
Alzheimers Dement. 2023 Dec;19(12):5952-5969. doi: 10.1002/alz.13463. Epub 2023 Oct 14.
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.
ML approaches are being developed in dementia prevention. We discuss exemplar uses and evaluate the current applications and limitations in the dementia prevention field.
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.
ML is not yet widely used but has considerable potential to enhance precision in dementia prevention.
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.
已确定多种可改变的痴呆风险因素。这些风险因素、它们之间或与遗传风险之间的可能相互作用以及因果关系，以及它们如何有助于临床试验招募和药物开发，仍存在很大争议。人工智能（AI）和机器学习（ML）可能会改进对这些因素的理解。
ML 方法正在被应用于痴呆预防。我们讨论了典型的用途，并评估了当前在痴呆预防领域的应用和局限性。
风险评估工具可能有助于确定临床试验的高危人群；然而，其性能需要改进。基于 ML 模型的新的风险评估和试验招募工具可能有助于降低成本并改善未来的试验。ML 可以为药物重新定位和疾病修饰治疗的优先级提供信息。
ML 在痴呆预防领域尚未得到广泛应用，但具有很大的潜力来提高精准性。
人工智能（AI）在痴呆预防领域尚未广泛应用。风险评估工具尚未在临床实践中使用。需要因果关系洞察来了解整个生命周期的风险因素。AI 将有助于为痴呆预防量身定制风险管理工具。AI 可以针对最有可能从临床试验中获益的特定患者群体。
