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Updated: Apr 10, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Proposal for a neuropsychological cognitive evaluation battery for detecting and distinguishing between mild
Pilar Luna-Lario1, Leire Azcárate-Jiménez, Raquel Seijas-Gómez
1Complejo Hospitalario de Navarra , Pamplona, Espana.
Abstract:
The early and etiological diagnosis of dementia syndrome in the clinical practice remains the neuropsychological assessment through the study of the cognitive profile of the patient and the qualitative and quantitative analysis of the functions, both impaired and preserved. In this article, we describe a neuropsychological battery of cognitive evaluation to detect mild cognitive impairment in any of its clinical forms and dementia; as well as discriminate between the main profiles of dementia syndrome, based on its topographic and etiological classification (frontotemporal, temporoparietal, subcortical, cortico-subcortical and multifocal). This battery is implemented in the neuropsychological assessment specialized surgery from Navarra Hospital Center Neurology Service. Not only the tests that form the assessment protocol are presented, but also the theoretical models that are considered more appropriate for their interpretation.
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