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Review
. 2024 Aug;44(8):3331024241268290.
doi: 10.1177/03331024241268290.

Artificial intelligence and headache

Anker Stubberud  1   2 , Helge Langseth  1   3 , Parashkev Nachev  4 , Manjit S Matharu  1   5 , Erling Tronvik  1   2   6
Affiliations
Review

Artificial intelligence and headache

Anker Stubberud et al. Cephalalgia. 2024 Aug.

Abstract

Background and methods: In this narrative review, we introduce key artificial intelligence (AI) and machine learning (ML) concepts, aimed at headache clinicians and researchers. Thereafter, we thoroughly review the use of AI in headache, based on a comprehensive literature search across PubMed, Embase and IEEExplore. Finally, we discuss limitations, as well as ethical and political perspectives.

Results: We identified six main research topics. First, natural language processing can be used to effectively extract and systematize unstructured headache research data, such as from electronic health records. Second, the most common application of ML is for classification of headache disorders, typically based on clinical record data, or neuroimaging data, with accuracies ranging from around 60% to well over 90%. Third, ML is used for prediction of headache disease trajectories. Fourth, ML shows promise in forecasting of headaches using self-reported data such as triggers and premonitory symptoms, data from wearable sensors and external data. Fifth and sixth, ML can be used for prediction of treatment responses and inference of treatment effects, respectively, aiming to optimize and individualize headache management.

Conclusions: The potential uses of AI and ML in headache are broad, but, at present, many studies suffer from poor reporting and lack out-of-sample evaluation, and most models are not validated in a clinical setting.

Keywords: decision-support; machine learning; migraine; prediction; tension-type headache; trigeminal autonomic cephalalgia.

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Conflict of interest statement

Declaration of conflicting interestsAnker Stubberud has received lecture honoraria from TEVA. AS holds a patent related to Cerebri developed by Nordic Brain Tech AS, an app intervention that includes headache forecasting. In addition, AS may benefit financially from a license agreement between Nordic Brain Tech AS and NTNU. Helge Langseth reports no conflicts of interest. Parashkev Nachev is funded by Wellcome and the NIHR BRC Biomedical Research Centre. He has shareholdings in two university spin-outs, Sonalis and Hologen. Manjit S. Matharu is chair of the medical advisory board of the CSF Leak Association; has served on advisory boards for AbbVie, Eli Lilly, Kriya, Lundbeck, Pfizer, Salvia and TEVA; has received payment for educational presentations from AbbVie, Eli Lilly, Lundbeck, Pfizer and TEVA; has received grants from Abbott, Medtronic and Ehlers Danlos Society; and has a patent on system and method for diagnosing and treating headaches (WO2018051103A1, issued). Erling Tronvik has received personal fees for lectures/advisory boards: Novartis, Eli Lilly, Abbvie, TEVA, Roche, Lundbeck, Pfizer, Biogen. Consultant for and owner of stocks and IP in Man & Science. Stocks and IP in Nordic Brain Tech (includes headache forecasting) and Keimon Medical. Non-personal research grants from several sources, including EU, Norwegian Research Council, Dam foundation, KlinBeForsk. Commissioned research (non-personal): Lundbeck, Eli-Lilly.

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