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Updated: Jul 3, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Early detection of mild cognitive impairment in the aged]
Ma del Díaz Mardomingo1, Herminia Peraita Adrados
1Facultad de Psicología, Universidad Nacional de Educación a Distancia, Madrid, Spain. mcdiaz@psi.uned.es
Abstract:
The data provided by this study are from the first evaluation of a sample of 140 subjects aged between 58 and 87 years carried out in the Autonomous Region of Madrid to detect early mild cognitive impairment (MCI). A description of the study methodology and design is accompanied by the results of the initial classification of the participants into healthy participants and participants with MCI. The latter were further classified as amnesic MCI, non-amnesic MCI, and mixed MCI, and the classification according to the psychometric criteria used was compared with the result of a cluster analysis performed on the standardized scores of the test battery. The results indicate that the MCI subgroups, contrary to their definition in the scientific literature, do not have clear limits.
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