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Headache disorders are among the most prevalent medical conditions worldwide. The diagnosis of headache disorders is based on medical history taking. Digital solutions such as natural language processing (NLP) may be of aid to understand the linguistic aspects of headache attack and headache related disability descriptions by patients. Participants will provide a written description of their headache disorder. The results will hopefully lead to a better understanding of the potential use of NLP in headache disorders.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Participants | Participants filling in the questionnaires |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Questionnaires | Other | Headache attack descriptions, Headache related disability descriptions, Questionnaires, MIDAS, MSQv2.1, SF36 |
|
| Measure | Description | Time Frame |
|---|---|---|
| Lexical diversity and differences between migraine and cluster headache | Chi-square measurement of a word token used by migraine patients versus cluster headache patients | through study completion, an average of 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of machine learning experiments for the correct classification of headache disorders | Machine learning experiments to investigate the potential to build modelling algorithms that accurately classify the self-given diagnosis by the patient based on text. | through study completion, an average of 1 year |
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Inclusion Criteria:
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Patients with headache disorders
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Hospital, Ghent: Department of Neurology | Ghent | 9000 | Belgium |
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| F1 scores of machine learning experiments for the correct classification of headache disorders |
Machine learning experiments to investigate the potential to build modelling algorithms that accurately classify the self-given diagnosis by the patient based on text. |
| through study completion, an average of 1 year |
| Word counts | Counts of word tokens of different headache disorder groups | through study completion, an average of 1 year |
| Sentences counts | Counts of sentence tokens of different headache disorder groups | through study completion, an average of 1 year |
| Paragraph counts | Counts of paragraph tokens of different headache disorder groups | through study completion, an average of 1 year |
| Term-frequency inverse document frequency scores (TF-IDF) | TF-IDF scores of word tokens of different headache disorder groups | through study completion, an average of 1 year |
| Migraine Disabillity Assessment [MIDAS] score calculation with text input | Machine learning experiments to investigate the potential to build modelling algorithms that accurately predict the impact score from Migraine Disabillity Assessment [MIDAS] based on text. | through study completion, an average of 1 year |
| Migraine Specific Questionaire versie 2.1 [MSQv2.1] score calculation with text input | Machine learning experiments to investigate the potential to build modelling algorithms that accurately predict the impact score from Migraine Specific Questionaire versie 2.1 [MSQv2.1] based on text. | through study completion, an average of 1 year |
| RAND SF-36 Dutch version score calculation with text input | Machine learning experiments to investigate the potential to build modelling algorithms that accurately predict the impact score from RAND SF-36 Dutch version based on text. | through study completion, an average of 1 year |
| ID | Term |
|---|---|
| D020773 | Headache Disorders |
| D018781 | Tension-Type Headache |
| D008881 | Migraine Disorders |
| D003027 | Cluster Headache |
| D051271 | Headache Disorders, Secondary |
| D006261 | Headache |
| ID | Term |
|---|---|
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D051270 | Headache Disorders, Primary |
| D051303 | Trigeminal Autonomic Cephalalgias |
| D010146 | Pain |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D011795 | Surveys and Questionnaires |
| ID | Term |
|---|---|
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D017531 | Health Care Evaluation Mechanisms |
| D011787 | Quality of Health Care |
| D017530 | Health Care Quality, Access, and Evaluation |
| D011634 | Public Health |
| D004778 | Environment and Public Health |
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