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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Longitudinal Changes in Performance on Cognitive Screening Tests in Patients with Mild Cognitive Impairment and
Fangzhou Li1, Hajime Takechi1,2, Atsuko Kokuryu1
1Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Background:
Neuropsychological tests that can track changes in cognitive functions after diagnosis of Alzheimer disease (AD) and mild cognitive impairment (MCI), including episodic memory, should be further developed.
Methods:
The participants of our study consisted of 22 mild AD patients and 11 MCI patients. They were followed up for 2 years. Brief cognitive screening tests were administered to the participants. Longitudinal changes in test performance were evaluated and analyzed.
Results:
In this longitudinal study, the Scenery Picture Memory Test (SPMT) showed significant changes over 2 years in both MCI and AD participants. The Mini-Mental State Examination (MMSE) and Word Fluency Test-vegetable showed significant changes only in AD participants. Other tests all showed little or no decline in results.
Conclusions:
The SPMT can be a useful tool for effectively observing changes during follow-up of MCI and AD patients.
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