Abstract
INTRODUCTION: Headaches are the main reason for visits to Neurology clinics, and migraine is the most common primary headache. with migraine being the most frequent. Our objective was to develop a computer application (app) that could empower Primary Health Care (PHC) physicians in decision-making regarding migraine. MATERIAL AND METHODS: A rule-based artificial intelligence system was designed to process patients' responses to the ID-Migraine screener and subsequently determine whether they met the diagnostic criteria for migraine or tension-type headache, according to the International Headache Society. The application, known as CefaleApp, is designed to generate a diagnosis of migraine, tension-type headache, or mixed headache. RESULTS: CefaleApp was validated in 152 patients referred from PHC clinics with a suspected diagnosis of migraine or tension-type headache. Patients were evaluated in the Neurology Department of a secondary-level hospital and in two regional hospitals. Agreement between the diagnosis generated by CefaleApp and that issued by an expert headache neurologist (gold standard) was estimated using Cohen's Kappa index and the Matthews correlation coefficient (MCC). Overall diagnostic accuracy was 90.8% (95% CI: 85.1-94.6%), Cohen's Kappa index was 0.73 (95% CI: 0.59-0.87), and the MCC value was 0.73. CONCLUSIONS: The migraine diagnosis generated by CefaleApp shows substantial-high agreement with that provided by the expert headache neurologist.