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Application of Artificial Intelligence in the Headache Field

  • Keiko Ihara
  • , Gina Dumkrieger
  • , Pengfei Zhang
  • , Tsubasa Takizawa
  • , Todd J. Schwedt
  • , Chia Chun Chiang

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose of Review: Headache disorders are highly prevalent worldwide. Rapidly advancing capabilities in artificial intelligence (AI) have expanded headache-related research with the potential to solve unmet needs in the headache field. We provide an overview of AI in headache research in this article. Recent Findings: We briefly introduce machine learning models and commonly used evaluation metrics. We then review studies that have utilized AI in the field to advance diagnostic accuracy and classification, predict treatment responses, gather insights from various data sources, and forecast migraine attacks. Furthermore, given the emergence of ChatGPT, a type of large language model (LLM), and the popularity it has gained, we also discuss how LLMs could be used to advance the field. Finally, we discuss the potential pitfalls, bias, and future directions of employing AI in headache medicine. Summary: Many recent studies on headache medicine incorporated machine learning, generative AI and LLMs. A comprehensive understanding of potential pitfalls and biases is crucial to using these novel techniques with minimum harm. When used appropriately, AI has the potential to revolutionize headache medicine.

Original languageEnglish
Pages (from-to)1049-1057
Number of pages9
JournalCurrent Pain and Headache Reports
Volume28
Issue number10
DOIs
Publication statusPublished - 2024 Oct

Keywords

  • Artificial intelligence
  • ChatGPT
  • Headache
  • Large language model
  • Machine learning
  • Migraine

ASJC Scopus subject areas

  • Clinical Neurology
  • Anesthesiology and Pain Medicine

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