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There have been studies about decision rules guiding the clinical diagnosis of Alzheimer’s
dementia (Jack et al. 2018, Bennett et al. 2006). Alzheimer’s dementia poses great
socioeconomic burden for the world. Our aim is to assess the potential of machine
learning approaches for classification of healthy (HV), mild cognitively impaired
(MCI) and Alzheimer’s dementia individuals using neuropsychological tests; while optimizing
the combination of tests that can be affordably implemented expeditiously and accurately
in the community to classify and diagnose Alzheimer’s dementia.
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