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Updated: Apr 23, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Risk factors and screening methods for detecting dementia: a narrative review
Blossom C M Stephan1, Carol Brayne2
1Institute of Healthy and Society, Newcastle University, UK.
Abstract:
Accurate detection of individuals with cognitive impairment and dementia in addition to identification of those at high risk of future disease is important to guide clinical care, and has research implications regarding clinical trial recruitment and development of dementia preventative strategies. In this narrative review, we describe new proposed criteria for early diagnosis of Alzheimer's disease (AD). We also explore risk factors for dementia and evaluate methods for screening for increased risk of incident disease. We highlight variability in different diagnostic approaches. Additional work needs to be done to validate new methods across different settings (such as population-based, primary care, and memory clinics), age, and ethnic groups. Having an accurate method to assess for dementia and predict risk in routine clinical care will aid decision making and could ultimately lead to disease prevention.
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