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Updated: Jun 25, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Rapid screening of cognitive change in patients with questionable dementia using the Memory Impairment Screen and the
Gilles Chopard1, Geraldine Vanholsbeeck, Gregory Tio
1Department of Neurology, Besançon University Hospital-Jean Minjoz, Besançon, France.
Objectives:
To assess the efficacy of combining the Memory Impairment Screen (MIS) and the Isaacs Set Test (IST) in predicting short-term development of dementia in a group of people with questionable dementia (QD) at baseline.
Design:
Performances of the weighted sum of MIS and IST and the <
Setting:
Database of the Regional Network for Diagnostic Aid and Management of Patients with Cognitive Impairment in the Franche-Comté geographical area in France.
Participants:
A cohort of 106 patients aged 65 and older with QD were followed up for a mean of 14.9 months (range 6-24 months).
Measurements:
Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the combination of these two tests.
Results:
The weighted sum had a sensitivity of 0.74 and a specificity of 0.84. The <
Conclusion:
This quickly performed tool (5 minutes) is simple to use and score. When including cutscores (MIS<6 or IST<25) or range values, this test could be considered a useful screening procedure for all types of dementias.
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