ArticleAphasiology2022
Enhancing the Classification of Aphasia: A Statistical Analysis Using Connected Speech.
Article in Aphasiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Contribution of artificial intelligence research to the development of inclusive applications for people with disabilities: A scoping review (2015-2025).PLOS digital health · 2026Article
- Discourse Measures From the Modern Cookie Theft Picture Description Are Sensitive to Mild Communication Deficits Not Captured by the Western Aphasia Battery-Revised Aphasia Quotient.American journal of speech-language pathology · 2025Article
- Data-driven classification of narrative speech characteristics in stroke aphasia distinguishes neurological and strategic contributions.Cortex; a journal devoted to the study of the nervous system and behavior · 2025Article
- An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications.Perspectives of the ASHA special interest groups · 2025Article
- Quality of Assessment Tools for Aphasia: A Systematic Review.Brain sciences · 2025Review
- Neural Predictors for the Generalization of Semantic and Phonological Treatment to Discourse Performance in Chronic Post-Stroke Aphasia.Neurobiology of language (Cambridge, Mass.) · 2025Article
- Three mechanisms of language comprehension are revealed through cluster analysis of individuals with language deficits.NPJ science of learning · 2024Article
- Automated Analysis of Fluency Behaviors in Aphasia.Journal of speech, language, and hearing research : JSLHR · 2024Article
- Clinical efficacy of pre-trained large language models through the lens of aphasia.Scientific reports · 2024Article
- Connected Speech Fluency in Poststroke and Progressive Aphasia: A Scoping Review of Quantitative Approaches and Features.American journal of speech-language pathology · 2024Article
- Lexical markers of disordered speech in primary progressive aphasia and 'Parkinson-plus' disorders.Brain communications · 2024Article
- Article
- Agrammatic output in non-fluent, including Broca's, aphasia as a rational behavior.Aphasiology · 2023Article
- Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts.Journal of speech, language, and hearing research : JSLHR · 2022Article
Corrections and comments
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Authors and funding
5 authors.
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Abstract
Background: Large shared databases and automated language analyses allow for the application of new data analysis techniques that can shed new light on the connected speech of people with aphasia (PWA). Aims: To identify coherent clusters of PWA based on language output using unsupervised statistical algorithms and to identify features that are most strongly associated with those clusters. Methods & Procedures: Clustering and classification methods were applied to language production data from 168 PWA. Language samples were from a standard discourse protocol tapping four genres: free speech personal narratives, picture descriptions, Cinderella storytelling, procedural discourse. Outcomes & Results: Seven distinct clusters of PWA were identified by the K-means algorithm. Using the random forests algorithm, a classification tree was proposed and validated, showing 91% agreement with the cluster assignments. This representative tree used only two variables to divide the data into distinct groups: total words from free speech tasks and total closed class words from the Cinderella storytelling task. Conclusion: Connected speech data can be used to distinguish PWA into coherent groups, providing insight into traditional aphasia classifications, factors that may guide discourse research and clinical work.
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