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Updated: Feb 8, 2026
12:18
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
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Using Informant and Performance Screening Methods to Detect Mild Cognitive Impairment and Dementia
1Comprehensive Center for Brain Health and Institute for Healthy Aging and Lifespan Studies, Charles E. Schmidt College of Medicine and Christine E. Lynn College of Nursing, Florida Atlantic University.
Current Geriatrics Reports
|July 3, 2018
Summary
Community dementia detection is difficult. This review offers a practical algorithm combining performance, informant, and self-reports for effective dementia screening in clinical settings.
Area of Science:
- Gerontology
- Neurology
- Cognitive Science
Background:
- Community-based dementia detection presents significant challenges.
- Early identification of cognitive impairment is crucial for timely intervention and management.
Purpose of the Study:
- To review existing dementia screening methods.
- To propose a practical algorithm for dementia screening across diverse clinical environments.
Main Methods:
- Review of recently developed brief performance-based assessments.
- Inclusion of informant-based assessments for comprehensive evaluation.
- Integration of patient self-report measures for subjective cognitive impairment detection.
Main Results:
- Validated performance and informant assessments are available.
- Patient self-reports can identify subjective cognitive decline.
- Combined approaches enhance screening accuracy.
Conclusions:
- An optimal dementia screening strategy integrates performance, informant, and self-report data.
- These assessments can be efficiently administered in clinical waiting areas.
- This comprehensive data aids in diagnosis, staging, and management planning.
Keywords:
AD8Alzheimer’s diseaseMontreal Cognitive AssessmentScreeningdementiamild cognitive impairmentquick dementia rating systemMore Related Videos
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