Pınar Yalınay Dikmen, Elif Ilgaz Aydinlar, Seda N Dumlu, Tugay Onal, Salih Gumru, Efe Onganer, Alex Loleyt
AI-assisted EHR analysis revealed underdiagnosis, high imaging use, and limited adoption of mechanism-specific preventives in Türkiye, underscoring the need for improved diagnostic accuracy and broader access to modern therapies.
BACKGROUND: Despite available diagnostic and therapeutic options, a major unmet need persists in migraine care. This study applied artificial intelligence (AI) to extract structured insights from routine care and assess migraine burden, diagnosis, and treatment in Türkiye.
METHODS: The Türkiye Migraine Registry Study was a retrospective, observational study across 23 hospitals and clinics in eight cities. Anonymized electronic health records (EHRs) of 11,023 adults treated between January 2021 and October 2023 were analyzed. A validated AI framework with natural language processing and machine learning extracted demographics, comorbidities, imaging, and prescriptions. Descriptive statistics summarized outcomes.
RESULTS: Of 90,381 neurology patients, 16,751 (18.5%) had migraine or suspected migraine; 11,023 met inclusion. Only 46.9% carried an ICD-10 migraine code, while 53.1% were coded under other headache syndromes yet frequently received migraine-specific therapies. The cohort was 73% female, mean age 41.5. Neuroimaging was frequent (58.7% MRI, 15.2% CT), and 18.4% visited emergency care. Preventive therapy was prescribed to 63.7%, mainly antidepressants (31.4%) and beta-blockers (19.4%). OnabotulinumtoxinA and CGRP monoclonal antibodies were used in 10.3 and 3.4%.
CONCLUSION: AI-assisted EHR analysis revealed underdiagnosis, high imaging use, and limited adoption of mechanism-specific preventives in Türkiye, underscoring the need for improved diagnostic accuracy and broader access to modern therapies.