Benchmarking State-of-the-Art Large Language Models for Migraine Patient Education: A Comparison of Performances on the Responses to Common Queries.

Migraine, a frequent and highly disabling disorder, necessitates enhanced education of individuals with migraine to mitigate this global burden. The rapidly evolving field of large language models (LLMs) presents a promising avenue for assisting in migraine patient education. This study aims to assess the potential of LLMs in this context by evaluating the accuracy of responses from five leading LLMs, including OpenAI's ChatGPT 3.5 and 4.0, Google Bard, Meta Llama2, and Anthropic Claude2, in addressing 30 commonly asked migraine-related queries. We found that LLMs demonstrated varied levels of accuracy. ChatGPT-4.0 provided 96.7% appropriate responses, while other chatbots provided 83.3% to 90% appropriate responses (Pearson's chi-squared test, P=0.481). Additionally, Google Bard had a 'poor' rating proportion of 6.7%, other LLMs had 3.3% (Pearson's chi-squared test, P=0.961). This study underscores the potential of LLMs to accurately address common migraine-related queries. Such findings could advance AI-assisted education for individuals with migraine, providing insights for a holistic approach to migraine management.