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Updated: Aug 18, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Validation of a novel computerized cognitive function test for the rapid detection of mild cognitive impairment
Minoru Kouzuki1, Madoka Miyamoto2, Nobuto Tanaka2
1Department of Biological Regulation, School of Health Science, Faculty of Medicine, Tottori University, 86 Nishi-cho, Yonago, 683-8503, Japan. kouzuki@tottori-u.ac.jp.
Background:
In the present study, we examined the distinguishing ability of a mild cognitive impairment (MCI) assessment tool for rapid screening using a computer (MARC) for Alzheimer's disease dementia (ADD), MCI, and non-demented controls (NDC) with no cognitive impairment, as well as its validity and reliability, as part of a preliminary trial for the development of the tool.
Methods:
A total of 64 participants (23 in the ADD group, 17 in the MCI group, and 24 in the NDC group) were analyzed. The participants were administered MARC and a pre-existing computerized Alzheimer's dementia screening test (MSP), and 31 participants (14 in the MCI group, 17 in the NDC group) were readministered MARC within 4 months from the first test.
Results:
The median (interquartile range) test time for MARC was 401 (350-453) s. Total MARC scores were significantly worse in the MCI and ADD groups than in the NDC group (p < 0.05 and p < 0.01, respectively). In the receiver operating characteristic (ROC) analysis, the area under the ROC curve (AUC) when comparing the NDC and MCI groups was 0.866 (95% CI, 0.759-0.974), when comparing the NDC and AD groups was 0.989 (95% CI, 0.970-1.000), and when comparing the MCI and AD groups was 0.889 (95% CI, 0.790-0.988). Furthermore, there was a significant correlation with the results of the existing test, MSP (r = 0.839, p < 0.001). In addition, the intraclass correlation coefficient (ICC) (1,1) when the first and second MARC scores were compared was 0.740 (95% CI, 0.529-0.865; p < 0.001).
Conclusions:
MARC is considered capable of distinguishing MCI with high accuracy. The tool has good validity and reliability, and it can be administered in a short period of time without the need for a specialist.
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