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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Computerized cognitive assessment of mild cognitive impairment in urban African Americans
Glen M Doniger1, Mi-Yeoung Jo, Ely S Simon
1Department of Clinical Science, NeuroTrax Corporation, Newark, New Jersey 07103, USA. glen.doniger@neurotrax.com
Abstract:
Few objective cognitive assessment tools have been validated for mild cognitive impairment (MCI) in African Americans despite higher prevalence of disease. This preliminary study evaluated discriminant validity of a computerized cognitive assessment battery for MCI in an urban African American cohort. Twenty-seven participants with MCI and 22 cognitively healthy individuals completed a multidomain battery (Mindstreams, NeuroTrax Corp, New Jersey). Mild cognitive impairment participants performed more poorly than cognitively healthy participants in all domains, with significant differences in memory (P = .003; d = 0.96), executive function (P = .046; d = 0.64), and overall battery performance (P = .041; d = 0.63). Adjustment for intelligence quotient (IQ) yielded significant differences in memory (P < .001; d = 1.34), executive function (P = .007; d = 0.86), attention (P = .014; d = .80), and overall performance (P = .001; d = 1.09). Such a validated battery may help to address an important clinical need in this population.
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