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Updated: Jul 19, 2026
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Mild cognitive impairment: what's in a name?
E Dierckx1, S Engelborghs, R De Raedt
1Developmental and Lifespan Psychology, Vrije Universiteit Brussel, Brussels, Belgium. eva.dierckx@vub.ac.be
Gerontology
|September 22, 2006
Summary
Mild cognitive impairment (MCI) is a heterogeneous syndrome. This review suggests incorporating neuropsychological tests and depressive symptoms into diagnostic criteria to improve MCI identification in the elderly.
Area of Science:
- Neuropsychology
- Geriatric Medicine
- Cognitive Science
Background:
- Mild cognitive impairment (MCI) bridges normal aging and dementia but lacks standardized criteria.
- Current diagnostic approaches, like Petersen's criteria, are widely used but require refinement.
- The interplay between MCI and depression in older adults remains under-explored.
Purpose of the Study:
- To address concerns regarding the conceptualization of MCI.
- To propose guidelines for neuropsychological assessment of MCI.
- To examine the relationship between elderly depression and MCI.
Main Methods:
- Review of existing literature and diagnostic criteria for MCI.
- Hypothesizing the utility of specific neuropsychological instruments.
- Suggesting modifications to diagnostic flowcharts.
Main Results:
- Certain neuropsychological tests can operationalize Petersen's MCI criteria.
- Cued recall memory tests may distinguish progressive from non-progressive MCI.
- Elderly depression with cognitive deficits aligns with MCI characteristics.
Conclusions:
- Integrating specific neuropsychological instruments enhances MCI diagnosis.
- Including depressive symptoms in diagnostic criteria improves MCI identification.
- Proposed adjustments offer practical tools for clinicians diagnosing MCI.
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