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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT05204316
Other study ID # BC-10619
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date January 13, 2022
Est. completion date December 31, 2023

Study information

Verified date May 2024
Source University Hospital, Ghent
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

The research collects spoken descriptions of headache disorders by participants with headache disorders. The speech recordings are analyzed by natural language processing (NLP) tools to analyse linguistic properties of the texts and to obtain insight into the potential of NLP machine learning models for the recognition of headache syndromes of the participants.


Recruitment information / eligibility

Status Completed
Enrollment 2
Est. completion date December 31, 2023
Est. primary completion date December 31, 2023
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - is a patient of the tertiary headache clinic at Ghent University Hospital - is 18 years or older - has Dutch as native speaking language Exclusion Criteria: - has difficulties in producing spoken language - has limited or no knowledge of Dutch

Study Design


Related Conditions & MeSH terms


Intervention

Other:
Digital Analysis of Speech
Recordings will be transcribed manually to written digital text formats, on which NLP tools such as tokenisation and lexical analysis will be performed.

Locations

Country Name City State
Belgium UZ Gent - Dienst Neurologie Gent

Sponsors (1)

Lead Sponsor Collaborator
University Hospital, Ghent

Country where clinical trial is conducted

Belgium, 

Outcome

Type Measure Description Time frame Safety issue
Primary Linguistic analysis of texts Descriptive linguistic analysis of lexical choices, sentence formation and thematic content within the texts through study completion, an average of 1 year
Secondary Machine learning modelling for classification of headache disorders To investigate the potential and learn insights of machine learning modelling to classify headache disorders based on the descriptions by participants through study completion, an average of 1 year
Secondary Machine learning modelling for estimation of headache impact scores To investigate the potential and learn insights of machine learning modelling to estimate headache impact scores from different validated questionnaires investigating burden of disease and quality of life through study completion, an average of 1 year
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