Migraine affects 1 in 7 people globally, significantly impacting quality of life and economic productivity. Despite its prevalence, limited awareness leads to misdiagnosis, inadequate treatment, and stigmatization. AI can enhance migraine management through improved diagnosis, prediction, and personalized education. The primary objective of this study is to determine if adding AI-assisted migraine education to standard education improves patients' understanding of their condition more effectively.

Migraine affecting approximately 1 in 7 individuals globally, significantly impacts quality of life and economic productivity due to its associated healthcare and social burdens. Despite its prevalence, awareness and understanding of migraine remain limited, contributing to misdiagnosis, inadequate treatment, and the perpetuation of stigmatization.

Artificial Intelligence (AI) may advance migraine management by improving diagnosis, prediction, and educational outreach. AI applications are currently being employed in diagnosing migraines more accurately by analyzing comprehensive patient data, thus differentiating migraine from other types of headaches. Additionally, AI algorithms predict migraine episodes, enabling preemptive measures. They also streamline medication management through reminders and monitor patient adherence, which is crucial for preventing medication overuse and optimizing treatment outcomes.

Moreover, AI can bridge the educational gap in migraine understanding. By using adaptive learning technologies, AI platforms can deliver personalized educational content, tailored to an individual's knowledge level and learning pace, enhancing understanding and engagement. This approach not only facilitates better management of the condition but also promotes a broader societal awareness essential for destigmatizing migraine.

The primary objective of this study is to ascertain if the addition of AI-assisted migraine education to standard migraine education yields a superior improvement in the patients' understanding of their condition.

Inclusion Criteria:

• aged between 18 and 65 years at the time of signing the informed consent
• Newly diagnosis of migraine, confirmed through the medical chart
• The participant must be capable of giving signed informed consent
• Access to a laptop, computer, smartphone, or tablet

Exclusion Criteria:

• Insufficient knowledge of the protocol language (italian)
• Patients with cognitive impairment and/or unable to use or access the AI-powered learning platform developed in this study.
• Vulnerable participants (e.g. minors, participants incapable of judgment or participants under tutelage)