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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Clarifying comparative claims in digital cognitive assessment: a matters arising on multimodal detection of cognitive
1Cognivue, Inc., Victor, NY, USA. pestes@cognivue.com.
Abstract:
Digital cognitive assessments represent an important and rapidly evolving approach to detecting cognitive impairment and Alzheimer's disease-related pathology. Jannati et al. report promising findings using a multimodal digital clock and recall assessment to identify cognitive impairment and amyloid positivity. While this contribution is welcomed, several comparative statements regarding Cognivue® rely on historical regulatory data and do not reflect the contemporaneous peer-reviewed evidence base available at the time of manuscript preparation. This Matters Arising article clarifies the limitations of cross-study performance comparisons, addresses selective citation of a single early Cognivue publication, and summarizes subsequent peer-reviewed findings demonstrating Cognivue's psychometric validity, biomarker associations, and generalizability across diverse populations. These considerations highlight the importance of harmonized, contemporaneous comparisons when asserting relative performance among digital cognitive assessment tools.
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