ArticleJournal of Alzheimer's disease : JAD2025
Speech-based digital cognitive assessments for detection of mild cognitive impairment: Validation against paper-based neurocognitive assessment scores.
Article in Journal of Alzheimer's disease : JAD, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- Speech-based digital cognitive assessment for clinical trials: Detecting cognitive impairment stages and AD biomarker relations across European cohorts.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Benchmarking speech biomarkers of Alzheimer's against cognitive and neural measures.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Exploring neural correlates of automated speech-based cognitive markers through resting-state functional connectivity in aging and at-risk Alzheimer's disease.Alzheimer's research & therapy · 2026Article
- Clinical translation of fluid, imaging, and digital biomarkers for Alzheimer's disease.Alzheimer's research & therapy · 2026Review
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Authors and funding
33 authors.
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Abstract
BackgroundCognitive decline in Alzheimer's disease (AD) often includes speech impairments, where subtle changes may precede clinical dementia onset. As clinical trials focus on early identification of patients for disease-modifying treatments, digital speech-based assessments for scalable screening have become crucial.ObjectiveThis study aimed to validate a remote, speech-based digital cognitive assessment for mild cognitive impairment (MCI) detection through the comparison with gold-standard paper-based neurocognitive assessments.MethodsWithin the PROSPECT-AD project, speech and clinical data were obtained from the German DELCODE and DESCRIBE cohorts, including 21 healthy controls (HC), 110 participants with subjective cognitive decline (SCD), and 59 with MCI. Spearman rank and partial correlations were computed between speech-based scores and clinical measures. Kruskal-Wallis tests assessed group differences. We trained machine learning models to classify diagnostic groups comparing classification accuracies between gold-standard assessment scores and a speech-based digital cognitive assessment composite score (SB-C).ResultsGlobal cognition, as measured by SB-C, significantly differed between diagnostic groups (
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