The Clinical Relevance of Artificial Intelligence in Migraine

Abstract

Migraine is a burdensome neurological disorder that still lacks clear and easily accessible diagnostic biomarkers. Furthermore, a straightforward pathway is hard to find for migraineurs’ management, so the search for response predictors has become urgent. Nowadays, artificial intelligence (AI) has pervaded almost every aspect of our lives, and medicine has not been missed. Its applications are nearly limitless, and the ability to use machine learning approaches has given researchers a chance to give huge amounts of data new insights. When it comes to migraine, AI may play a fundamental role, helping clinicians and patients in many ways. For example, AI-based models can increase diagnostic accuracy, especially for non-headache specialists, and may help in correctly classifying the different groups of patients. Moreover, AI models analysing brain imaging studies reveal promising results in identifying disease biomarkers. Regarding migraine management, AI applications showed value in identifying outcome measures, the best treatment choices, and therapy response prediction. In the present review, the authors introduce the various and most recent clinical applications of AI regarding migraine.

Artificial Intelligence as A Complementary Tool for Clincal Decision-Making in Stroke and Epilepsy

“…With its sophisticated machine learning algorithms, AI offers efficient and practical tools to clinicians to better interpret, access, and understand clinical information and narrow differential diagnoses in simple and complex cases [ 1 , 2 ]. AI has demonstrated great clinical utility in the management of Migraines as demonstrated by Torrente A. et al [ 3 ]. Due to a high incidence of Stroke and Epilepsy in United States, which have been leading causes of morbidity and mortality, we would like to focus, exhibit, and discuss potential applications of AI in these two fields specifically by presenting our literature review and innovations so far, which can serve as great clinical adjuncts for clinicians which, in turn, can help deliver excellent patient care.…”