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Updated: Aug 5, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The Future of Cognitive Screening in Neurodegenerative Diseases
Laura Glass Umfleet1, Robert M Bilder2, David W Loring3,4
1Department of Neurology, Medical College of Wisconsin, Wauwatosa, WI, USA.
Abstract:
Cognitive screening instruments (CSI) have variable sensitivity and specificity to the cognitive changes associated with dementia syndromes, and the most recent systematic review found insufficient evidence to support the benefit of cognitive screening tools in older adults residing within the community. Consequently, there is a critical need to improve CSI methods, which have not yet incorporated advances in psychometrics, neuroscience, and technology. The primary goal of this article is to provide a framework for transitioning from legacy CSIs to advanced dementia screening measurement. In line with ongoing efforts in neuropsychology and the call for next-generation digital assessment for early detection of AD, we propose a psychometrically advanced (including application of item response theory methods), automated selective assessment model that provides a framework to help propel an assessment revolution. Further, we present a three-phase model for modernizing CSIs and discuss critical diversity and inclusion issues, current challenges in differentiating normal from pathological aging, and ethical considerations.
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