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Updated: Sep 10, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The mild cognitive impairment window for optimal Alzheimer's disease intervention
Kevin Mekulu1, Faisal Aqlan2, Hui Yang1
1Complex Systems Monitoring, Modeling and Control Laboratory, Pennsylvania State University, University Park, PA, USA.
None:
The FDA approval of disease-modifying Alzheimer's disease therapies marks a major shift in treatment but exposes a critical challenge: identifying patients during the mild cognitive impairment (MCI) stage when intervention is most effective. Despite early biological changes, most diagnoses occur after significant decline. Drawing from over 180 stakeholder interviews conducted through the NSF I-Corps program reveal major detection gaps across primary care, specialty access, and available tools. This commentary highlights the consequences of delayed diagnosis and proposes translational strategies to align early detection with therapeutic opportunity, positioning MCI as the critical window for Alzheimer's disease intervention.
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