Back to Search
Start Over
Screening for Mild Cognitive Impairment Using a Machine Learning Classifier and the Remote Speech Biomarker for Cognition: Evidence from Two Clinically Relevant Cohorts.
- Source :
- Journal of Alzheimer's Disease; 2023, Vol. 91 Issue 4, p1165-1171, 7p
- Publication Year :
- 2023
-
Abstract
- Background: Modern prodromal Alzheimer's disease (AD) clinical trials might extend outreach to a general population, causing high screen-out rates and thereby increasing study time and costs. Thus, screening tools that cost-effectively detect mild cognitive impairment (MCI) at scale are needed. Objective: Develop a screening algorithm that can differentiate between healthy and MCI participants in different clinically relevant populations. Methods: Two screening algorithms based on the remote ki:e speech biomarker for cognition (ki:e SB-C) were designed on a Dutch memory clinic cohort (N = 121) and a Swedish birth cohort (N = 404). MCI classification was each evaluated on the training cohort as well as on the unrelated validation cohort. Results: The algorithms achieved a performance of AUC 0.73 and AUC 0.77 in the respective training cohorts and AUC 0.81 in the unseen validation cohorts. Conclusion: The results indicate that a ki:e SB-C based algorithm robustly detects MCI across different cohorts and languages, which has the potential to make current trials more efficient and improve future primary health care. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13872877
- Volume :
- 91
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Journal of Alzheimer's Disease
- Publication Type :
- Academic Journal
- Accession number :
- 161762793
- Full Text :
- https://doi.org/10.3233/JAD-220762