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Updated: Jun 17, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Pre-symptomatic detection of Alzheimer's disease and mild cognitive impairment]
1Institute of Development, Aging and Cancer, Tohoku University.
Abstract:
The clinical diagnosis of Alzheimer's disease (AD) is occasionally imprecise using consensus criteria for probable AD. Therefore, there is a great need for simple biomarkers that substantially aid early diagnosis and tract disease progression of AD and mild cognitive impairment. Of currently available biomarkers for AD, imaging markers are of particular importance based on their low invasiveness and reproducibility. In vivo detection of brain amyloid burden using positron emission tomography either by PIB or BF-227 would be quite attractive. In Japan, Alzheimer's disease neuroimaging initiatives (ADNI) has been launched in 2008 in accordance with US- and World-Wide ADNI. The paradigm of AD diagnosis and treatment would be shifted from "cognitive-based" to "biomarker-based" framework. The use of ideal biomarkers can remarkably speed up AD drug discovery by providing earliest signals of drug efficacy.
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