ArticleFrontiers in digital health2021
The Joint Effects of Acoustic and Linguistic Markers for Early Identification of Mild Cognitive Impairment.
Article in Frontiers in digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02871921 (Internet-based Conversational Engagement Clinical Trial), which is not on this map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Internet-based Conversational Engagement Clinical Trial
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic utility of speech-based biomarkers in mild cognitive impairment: a systematic review and meta-analysis.Age and ageing · 2025Pooled it
- Machine learning and natural language processing for the identification of potential mental disorders among school-age children: a prospective birth cohort study.BMC medicine · 2026Article
- Navigating the future of artificial intelligence technologies for improving the care of older adults.Innovation in aging · 2025Article
- Bridging Language Markers and Pathology: Correlations Between Digital Speech Measures and Surrogate CSF Biomarkers in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025Article
- Listening to the Mind: Integrating Vocal Biomarkers into Digital Health.Brain sciences · 2025Article
- Speech Acoustic Markers Can Detect Mild Cognitive Impairment in Parkinson's Disease.IEEE journal of selected topics in signal processing · 2025Article
- Remote Digital Technologies for the Early Detection and Monitoring of Cognitive Decline in Patients With Type 2 Diabetes: Insights From Studies of Neurodegenerative Diseases.Journal of diabetes science and technology · 2024Review
- Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module.Expert systems with applications · 2024Article
- Estimation of the Cognitive Functioning of the Elderly by AI Agents: A Comparative Analysis of the Effects of the Psychological Burden of Intervention.Healthcare (Basel, Switzerland) · 2024Article
- Article
- Temporal Harmonization: Improved Detection of Mild Cognitive Impairment from Temporal Language Markers using Subject-invariant Learning.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Subject Harmonization of Digital Biomarkers: Improved Detection of Mild Cognitive Impairment from Language Markers.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2024Article
- Detection of Mild Cognitive Impairment from Language Markers with Crossmodal Augmentation.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2023Article
- Bridging language markers and pathology: correlations between digital speech measures and surrogate CSF biomarkers in Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
In recent years, behavioral markers such as spoken language and lexical preferences have been studied in the early detection of mild cognitive impairment (MCI) using conversations. While the combination of linguistic and acoustic signals have been shown to be effective in detecting MCI, they have generally been restricted to structured conversations in which the interviewee responds to fixed prompts. In this study, we show that linguistic and acoustic features can be combined synergistically to identify MCI in semi-structured conversations. Using conversational data from an on-going clinical trial (Clinicaltrials.gov: NCT02871921), we find that the combination of linguistic and acoustic features on semi-structured conversations achieves a mean AUC of 82.7, significantly (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.