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Updated: Jun 4, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Mild cognitive impairment subcategories depend on the source of norms
Genevieve Arsenault-Lapierre1, Victor Whitehead, Sylvie Belleville
1Bloomfield Centre for Research on Aging, Lady Davis Institute of Medical Research, Sir B. Davis Jewish General Hospital, Montreal, QC, Canada.
Abstract:
The diagnosis of mild cognitive impairment (MCI) entails evidence of objective cognitive loss using neuropsychological measures. In this study, we examined whether the presence and degree of objective cognitive impairment varied according to the use of published versus local norms. We also varied the cutoff scores at which impairment was recognized and examined whether this altered inclusion in MCI subcategories. We found that the use of different comparison normative groups altered the subcategory diagnoses, especially when the cutoff score for impairment was conservative. In general, local norms were more stringent than published norms. We discuss the implications of these results for MCI diagnosis and categorization.
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