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Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning
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| Published in: | Journal of Headache and Pain |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1868847855519662080 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Journal of Headache and Pain |
| description | |
| discipline_display | Anaesthesiology |
| discipline_facet | Anaesthesiology |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:95314 |
| institution | FRELIP |
| journal_source_facet | Journal of Headache and Pain |
| last_indexed | 2026-06-24T03:36:40.561Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning Anaesthesiology General Anaesthesiology |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Anaesthesiology General Anaesthesiology |
| subject_facet | Anaesthesiology General Anaesthesiology |
| title | Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning |
| title_alt | Firmas de conectividad efectiva relacionadas con la corteza vestibular: caracterización y diferenciación de pacientes con migraña vestibular mediante resonancia magnética y aprendizaje automático Signatures de connectivité effective liées au cortex vestibulaire : caractérisation et différenciation des patients atteints de migraine vestibulaire via l'imagerie par résonance magnétique et l'apprentissage automatique Assinaturas de conectividade efetiva relacionadas ao córtex vestibular: caracterização e diferenciação de pacientes com enxaqueca vestibular via ressonância magnética e aprendizado de máquina |
| title_auth | Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning |
| title_es_txt | Firmas de conectividad efectiva relacionadas con la corteza vestibular: caracterización y diferenciación de pacientes con migraña vestibular mediante resonancia magnética y aprendizaje automático |
| title_fr_txt | Signatures de connectivité effective liées au cortex vestibulaire : caractérisation et différenciation des patients atteints de migraine vestibulaire via l'imagerie par résonance magnétique et l'apprentissage automatique |
| title_full | Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning |
| title_fullStr | Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning |
| title_full_unstemmed | Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning |
| title_pt_txt | Assinaturas de conectividade efetiva relacionadas ao córtex vestibular: caracterização e diferenciação de pacientes com enxaqueca vestibular via ressonância magnética e aprendizado de máquina |
| title_short | Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning |
| title_sort | vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning |
| topic | Anaesthesiology General Anaesthesiology |
| url | https://link.springer.com/article/10.1186/s10194-026-02430-y |