ŠUBERT, M., et al. Lexical and syntactic deficits analyzed via automated natural language processing: the new monitoring tool in multiple sclerosis. Therapeutic Advances in Neurological Disorders. 2023, 16 ISSN 1756-2856. DOI 10.1177/17562864231180719.
Background:Impairment of higher language functions associated with natural spontaneous speech in multiple sclerosis (MS) remains underexplored. Objectives:We presented a fully automated method for discriminating MS patients from healthy controls based on lexical and syntactic linguistic features. Methods:We enrolled 120 MS individuals with Expanded Disability Status Scale ranging from 1 to 6.5 and 120 age-, sex-, and education-matched healthy controls. Linguistic analysis was performed with fully automated methods based on automatic speech recognition and natural language processing techniques using eight lexical and syntactic features acquired from the spontaneous discourse. Fully automated annotations were compared with human annotations. Results:Compared with healthy controls, lexical impairment in MS consisted of an increase in content words (p = 0.037), a decrease in function words (p = 0.007), and overuse of verbs at the expense of noun (p = 0.047), while syntactic impairment manifested as shorter utterance length (p = 0.002), and low number of coordinate clause (p < 0.001). A fully automated language analysis approach enabled discrimination between MS and controls with an area under the curve of 0.70. A significant relationship was detected between shorter utterance length and lower symbol digit modalities test score (r = 0.25, p = 0.008). Strong associations between a majority of automatically and manually computed features were observed (r > 0.88, p < 0.001). Conclusion:Automated discourse analysis has the potential to provide an easy-to-implement and low-cost language-based biomarker of cognitive decline in MS for future clinical trials.
eng
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
SAGE PUBLICATIONS LTD
dc.relation.ispartof
Therapeutic Advances in Neurological Disorders
dc.subject
automated linguistic analysis
eng
dc.subject
language
eng
dc.subject
multiple sclerosis
eng
dc.subject
nature language processing
eng
dc.subject
spontaneous discourse
eng
dc.title
Lexical and syntactic deficits analyzed via automated natural language processing: the new monitoring tool in multiple sclerosis