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Updated: Aug 13, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A longitudinal study regarding conversion from mild memory impairment to dementia in a Japanese community
Tomohisa Ishikawa1, Manabu Ikeda, Naomi Matsumoto
1Department of Neuropsychiatry, Ehime University School of Medicine, Japan.
Objective:
To estimate the rate that subjects with Mild Memory Impairment /Not Dementia (MMI/ND) shifted to dementia in a population-based cohort and to establish simple diagnostic methods for identification of high-risk persons for dementia.
Methods:
Subjects in a community-based elderly cohort of MMI/ND were followed longitudinally. Subjects were selected from the participants in the first Nakayama study. MMI/ND was defined as memory deficit with objective memory assessment, without dementia, impairment of general cognitive function, or disability in activities of daily living. The conversion rate was calculated using the person-year method.
Results:
At baseline, the sample consisted of 104 subjects (59 female; 45 male) selected from 1,162 community dwellers aged over 65 year. During the five-year follow-up, 14 subjects died, 13 moved to other communities, and six refused to participate further. Eleven (10.6%) subjects were diagnosed with Alzheimer's disease (AD), five (4.8%) were diagnosed with vascular dementia (VaD), and six (5.8%) were diagnosed with dementia of other etiology. The annual conversion rate that MMI/ND shifted to AD is calculated on 8.5% per 100 person-year, and shifted to dementia on 16.1% per 100 person-year in this survey.
Conclusions:
The rate at which subjects with MMI/ND whose conditions shifted to dementia was the same as the rate that subjects with mild cognitive impairment (MCI) shifted to dementia in a previous report. It would be useful to identify groups of high-risk individuals for dementia by simple diagnostic methods.
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