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Voiceprints of cognitive impairment: analyzing digital voice for early detection of Alzheimer’s and related dementias
Neguine Rezaii, Bonnie Wong, Paul Aisen, Laurel A. Beckett, Jeffrey L. Dage, Ani Eloyan, Tatiana M. Foroud, Kyle B. Womack et al.. npj Dementia, 2025-11-03
Topic: Risk, prevention and care in population studies
Early detection of Alzheimer's disease (AD) is critical yet challenging, particularly in younger individuals. This study leverages artificial intelligence to analyze digital voice recordings from the Craft Story Recall task within the Longitudinal Early-onset AD Study (LEADS) to (1) detect cognitive impairment and (2) differentiate early-onset AD (EOAD) from early onset non-AD cognitive impairment (EOnonAD). Using speech samples from 120 patients and 68 cognitively unimpaired controls, we employed two classification approaches: feature-engineered machine learning and end-to-end deep learning incorporating a Large Language Model. To detect mild cognitive impairment, the feature-engineered model, using acoustic and linguistic features, achieved an AUC of 0.945 on the holdout test set, while the end-to-end model yielded an AUC of 0.988. For differentiating EOAD from EOnonAD, the feature-engineered model achieved an AUC of 0.804, and the end-to-end model yielded an AUC of 0.904 on the holdout set. Explainability analyses revealed reduced linguistic informativeness as a key AD indicator.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Rezaii, N., Wong, B., Aisen, P., Beckett, L. A., Dage, J. L., Eloyan, A., et al. (2025). Voiceprints of cognitive impairment: analyzing digital voice for early detection of Alzheimer’s and related dementias. npj Dementia. https://doi.org/10.1038/s44400-025-00040-0
Vancouver
Rezaii N, Wong B, Aisen P, Beckett LA, Dage JL, Eloyan A, et al. Voiceprints of cognitive impairment: analyzing digital voice for early detection of Alzheimer’s and related dementias. npj Dementia. 2025. doi:10.1038/s44400-025-00040-0. PMID: 41195302.
BibTeX
@article{rezaii2025-41195302,
author = {Rezaii, Neguine and Wong, Bonnie and Aisen, Paul and Beckett, Laurel A. and Dage, Jeffrey L. and Eloyan, Ani and Foroud, Tatiana M. and Womack, Kyle B. and others},
title = {{Voiceprints of cognitive impairment: analyzing digital voice for early detection of Alzheimer’s and related dementias}},
journal = {npj Dementia},
year = {2025},
doi = {10.1038/s44400-025-00040-0},
pmid = {41195302},
url = {https://doi.org/10.1038/s44400-025-00040-0}
}
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Key findings
- Explainability analyses revealed reduced linguistic informativeness as a key AD indicator.
Why it matters
Analyzing digital voice recordings, machine learning detected mild cognitive impairment with an AUC up to 0.988 and differentiated early-onset Alzheimer's from other early-onset cognitive impairment with an AUC up to 0.904. This is about early detection, not treating, curing or preventing the disease.
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Study details
- Study designlongitudinal study
- Participants120
- Evidence strengthModerate
How this study scored 55/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for effect reported and randomized / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (npj Dementia) |
| Journal's citation record | 0 / 4 | Npj Dementia: journal h-index 10 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 2 / 4 | 120 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 7 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 2.3 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 3 / 6 | Cited 4.4× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 7 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Kathy L. Newell: h-index 37 (OpenAlex, whole career) |
| Institution's track record | 3 / 3 | University of Washington: institution h-index 3,540 (OpenAlex) |
| Multicenter collaboration | 3 / 3 | OpenAlex lists 29 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41195302) |
| Free to read | 2 / 2 | Free to read |
| Total | 55 / 100 | — |
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Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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