Preventive strategies involving diet, lifestyle, and exercise can reduce dementia’s impact. Identifying individuals in the preclinical stage for treatment is essential. Amyloid deposition precedes clinical symptoms in Alzheimer’s disease (AD) by years, with cognitive symptoms resulting from oxidative stress, neuroinflammation, synaptic dysfunction, tau phosphorylation, and neuronal death. Early detection through neuropsychological tests, blood biomarkers, and functional neuroimaging can identify individuals at risk. By combining these markers with genetic and clinical risk factors using machine learning and AI, high-risk individuals can be identified for personalised prevention plans.
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