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Updated: Nov 21, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A new and short protocol to achieve the early diagnosis of mild cognitive impairment
Sara García1, Fernando Cuetos2, Antonello Novelli2,3,4
1Department of Psychology, University of Oviedo, Plaza Feijoo, s/n, 33003, Oviedo, Spain. saraggps@gmail.com.
Purpose:
The mild cognitive impairment (MCI) is a neurocognitive disorder which involves cognitive impairments beyond those expected for the age and education of the subject but are not significant enough to interfere with instrumental activities of daily living. The identification of individuals with MCI is particularly important for those who might benefit from new therapies. The aim of this work is to propose a comprehensive neuropsychological protocol to achieve early diagnosis of MCI.
Methods:
A neuropsychological battery was created and administered to a sample of patients with MCI (n = 25) and healthy matched controls (n = 25).
Results:
Although memory decline is often the first sign preceding the appearance of MCI, significant differences in visuospatial tasks, naming abilities, and executive function can be demonstrated as well between MCI and controls.
Conclusions:
A proper selection of cognitive measures within those included in the already-available neuropsychological batteries may provide a thorough assessment of MCI and allow its timely diagnosis.
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