Abstract：
OBJECTIVE: 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.
RESULTS: 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. 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.
RESULTS: 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. 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.
摘要：
目的：头痛疾病在世界范围内非常普遍。人工智能（AI）的快速发展已经扩大了与头痛相关的研究，有可能解决头痛领域未满足的需求。我们在本文中概述了人工智能在头痛研究中的应用。
结果：我们简要介绍了机器学习模型和常用的评估指标。然后，我们回顾了在该领域利用人工智能来提高诊断准确性和分类的研究，预测治疗反应，从各种数据源收集见解，并预测偏头痛发作。此外，考虑到ChatGPT的出现，一种大型语言模型(LLM)，以及它获得的受欢迎程度，我们还讨论了如何使用LLM来推进这一领域。最后,我们讨论潜在的陷阱，偏见，以及在头痛医学中使用人工智能的未来方向。最近许多关于头痛医学的研究都结合了机器学习，生成AI和LLM。全面了解潜在的陷阱和偏见对于以最小的伤害使用这些新技术至关重要。如果使用得当,AI有可能彻底改变头痛医学。
结果：我们简要介绍了机器学习模型和常用的评估指标。然后，我们回顾了在该领域利用人工智能来提高诊断准确性和分类的研究，预测治疗反应，从各种数据源收集见解，并预测偏头痛发作。此外，考虑到ChatGPT的出现，一种大型语言模型(LLM)，以及它获得的受欢迎程度，我们还讨论了如何使用LLM来推进这一领域。最后,我们讨论潜在的陷阱，偏见，以及在头痛医学中使用人工智能的未来方向。最近许多关于头痛医学的研究都结合了机器学习，生成AI和LLM。全面了解潜在的陷阱和偏见对于以最小的伤害使用这些新技术至关重要。如果使用得当,AI有可能彻底改变头痛医学。
