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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Assessment of cognition in early dementia
Nina B Silverberg1, Laurie M Ryan, Maria C Carrillo
1Division of Neuroscience, National Institute on Aging, National Institutes of Health, Bethesda MD.
Abstract:
Better tools for assessing cognitive impairment in the early stages of Alzheimer's disease (AD) are required to enable diagnosis of the disease before substantial neurodegeneration has taken place and to allow detection of subtle changes in the early stages of progression of the disease. The National Institute on Aging and the Alzheimer's Association convened a meeting to discuss state of the art methods for cognitive assessment, including computerized batteries, as well as new approaches in the pipeline. Speakers described research using novel tests of object recognition, spatial navigation, attentional control, semantic memory, semantic interference, prospective memory, false memory and executive function as among the tools that could provide earlier identification of individuals with AD. In addition to early detection, there is a need for assessments that reflect real-world situations in order to better assess functional disability. It is especially important to develop assessment tools that are useful in ethnically, culturally and linguistically diverse populations as well as in individuals with neurodegenerative disease other than AD.
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