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Updated: Oct 25, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Mild cognitive impairment history and current procedures in low- and middle-income countries: a brief review
Larissa Hartle1,2, Helenice Charchat-Fichman1
1Department of Psychology, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
Abstract:
Mild cognitive impairment (MCI) is a widely studied concept that has changed over time. Epidemiology, diagnosis, costs, prognostics, screening procedures, and categorization have been extensively discussed. However, unified guidelines are still not available, especially considering differences between low- and middle-income countries (LMIC) and high-income countries (HIC).
Objectives:
To contextualize and identify the main areas under investigation regarding MCI diagnosis and to investigate how much of the current knowledge is compatible with the diagnosis in an LMIC.
Methods:
This brief review followed the framework outlined for a scoping review and goes through the history of MCI and its diagnosis, the differences and relevance of LMIC research regarding the concept, and the current criteria for diagnosis.
Results:
Results show that the unique characteristics of LMIC influence the development of cognitive decline and how suitable procedures suggested by HIC can be used by LMIC to identify pathological aging processes in their early stages.
Conclusion:
Neuropsychological assessment of activities of daily living performance, considering the difference between omission and commission errors, is a more accessible course of action as a screening procedure for cognitive decline in LMIC.
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