ArticleProceedings of the conference. Association for Computational Linguistics. Meeting2020
Topic-Based Measures of Conversation for Detecting Mild Cognitive Impairment.
Article in Proceedings of the conference. Association for Computational Linguistics. Meeting, 2020. 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 12 papers.
What it found
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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
12 citing papers in PubMed, 15 citations in OpenAlex.
- Contrastive learning-based video quality assessment-jointed video vision transformer for video recognition.Neural computing & applications · 2026Article
- WATCH-SS: Developing a Trustworthy and Explainable Modular Framework for Detecting Cognitive Impairment from Spontaneous Speech.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2026Article
- Changes in conversational pattern as a clinical trial outcome: a proof-of-concept study using the I-CONECT data.Innovation in aging · 2026Article
- WATCH-SS: Developing a Trustworthy and Explainable Modular Framework for Detecting Cognitive Impairment from Spontaneous Speech.medRxiv : the preprint server for health sciences · 2025Article
- Introducing the Team Card: Enhancing governance for medical Artificial Intelligence (AI) systems in the age of complexity.PLOS digital health · 2025Article
- Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module.Expert systems with applications · 2024Article
- MC-ViViT: Multi-branch Classifier-ViViT to Detect Mild Cognitive Impairment in Older Adults Using Facial Videos.Expert systems with applications · 2024Article
- Subject Harmonization of Digital Biomarkers: Improved Detection of Mild Cognitive Impairment from Language Markers.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2024Article
- A pilot screening for cognitive impairment through voice technology (WAY2AGE).BMC psychology · 2023Article
- Predicting Progression from Normal to MCI and from MCI to AD Using Clinical Variables in the National Alzheimer's Coordinating Center Uniform Data Set Version 3: Application of Machine Learning Models and a Probability Calculator.The journal of prevention of Alzheimer's disease · 2023Article
- The Internet-Based Conversational Engagement Clinical Trial (I-CONECT) in Socially Isolated Adults 75+ Years Old: Randomized Controlled Trial Protocol and COVID-19 Related Study Modifications.Frontiers in digital health · 2021Article
- Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech.Frontiers in aging neuroscience · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Conversation is a complex cognitive task that engages multiple aspects of cognitive functions to remember the discussed topics, monitor the semantic and linguistic elements, and recognize others' emotions. In this paper, we propose a computational method based on the lexical coherence of consecutive utterances to quantify topical variations in semi-structured conversations of older adults with cognitive impairments. Extracting the lexical knowledge of conversational utterances, our method generates a set of novel conversational measures that indicate underlying cognitive deficits among subjects with mild cognitive impairment (MCI). Our preliminary results verify the utility of the proposed conversation-based measures in distinguishing MCI from healthy controls.
Identifiers
33642674PMC7909094W3046205455What OpenQuestion holds
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.