Natural Language Processing for Headache Medicine

NCT05377437 | Completed DMC

• 1 other identifier: BC-08263
• Study Type: interventional
• Target: 187
• Locations: 1 country
• Sites: 2

Brief Summary

Headache disorders are diagnosed by clinical history taking and applying the criteria provided within the International Classification of Headache Disorders Third Edition (ICHD-3). To help patients and physicians in making the correct diagnosis, digital technologies based on natural language processing (NLP) approaches may help to identify headache disorders within naturally patient-provided speech. The research aims to develop statistical models through machine-learning NLP applications for the accurate and precise classification of headache disorders with headache expert given ICHD-3 diagnosis as the gold standard. Furthermore, the research also aims to develop statistical models through machine-learning NLP applications for the estimation of impact scores derived from validated headache questionnaires by using texts as input. Patients from the tertiary headache clinic will be recruited to provide oral narrative textual descriptions of their headache attack characteristics and burden of disease related to their headache disorders. The goal of the research is to develop accessible, evidence-based digital medical tools as low-effort applications for the correct diagnosis of headache disorders and estimation of burden of disease due to headache disorders.

Conditions

Migraine; Headache Disorders

Keywords

Headache Disorders; Natural Language Processing

Outcome Measures

Primary Outcomes (1)

• F1-scores classification migraine narrative versus cluster headache narrative

  Machine learning classification models applying logistic regression, naive bayes classification and support vector machines based on the textual elements of the patients' narratives, to classify the provide narrative as either migraine or cluster headache. Higher F1-scores suggest better classification results.

  Baseline

Study Arms (1)

Participants

EXPERIMENTAL

Participants of the study

Other: Natural Language Processing

Interventions

Natural Language Processing OTHER

Natural Language Processing: classification and regression tasks.

Participants

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patients visiting the headache clinic of Ghent University Hospital for the first time or in follow up.
• Patients older than 18 years of age.
• Patients should be able to have Dutch as their mother tongue, and be sufficiently able to read, write, understand and speak Dutch.

You may not qualify if:

• Patients younger than 18 years of age.
• Patients with a language other than Dutch as mother tongue.
• Patients with substance abuse of alcohol or illicit drugs in the present or past.

Sponsors & Collaborators

• University Hospital, Ghent: lead

Study Sites (2)

Ghent University Hospital

Ghent, Belgie, 9000, Belgium

Location

University Hospital Ghent

Ghent, 9000, Belgium

Location

Related Publications (1)

• Vandenbussche N, Van Hee C, Hoste V, Paemeleire K. Using natural language processing to automatically classify written self-reported narratives by patients with migraine or cluster headache. J Headache Pain. 2022 Sep 30;23(1):129. doi: 10.1186/s10194-022-01490-0.

  PMID: 36180844 DERIVED

MeSH Terms

Conditions

Migraine Disorders; Headache Disorders

Condition Hierarchy (Ancestors)

Headache Disorders, Primary; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 25, 2022
• First Posted: May 17, 2022
• Study Start: August 28, 2020
• Primary Completion: December 31, 2023
• Study Completion: December 31, 2023
• Last Updated: May 16, 2024

Record last verified: 2024-05

Locations

BE (2)