The Emerging Clinical Relevance of Artificial Intelligence, Data Science, and Wearable Devices in Headache: A Narrative Review
This narrative review introduces key concepts in artificial intelligence (AI), data science, and wearable devices aimed at headache clinicians and researchers. PubMed and IEEEXplore were searched to identify relevant studies, and these were reviewed systematically. We identified six primary research...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Life |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1729/15/6/909 |
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| Summary: | This narrative review introduces key concepts in artificial intelligence (AI), data science, and wearable devices aimed at headache clinicians and researchers. PubMed and IEEEXplore were searched to identify relevant studies, and these were reviewed systematically. We identified six primary research topics. First, the most common application of AI and data science is in the diagnosis of headache disorders, with reported accuracies of up to 90%. Second, AI and data science are used for predicting headache disease trajectories and forecasting attacks. Third, prediction of treatment effects and data-driven individualization of treatment prescription demonstrate promising results, with accuracies ranging from 40% to 83%. Fourth, AI and data science can uncover hidden information within headache datasets, offering clinicians deeper insights. Fifth, wearables, combined with AI and data science, can improve remote monitoring and migraine management. Lastly, user experience studies indicate strong interest from both clinicians and patients in adopting these technologies. The potential applications of AI, data science, and wearable device technologies in headache research are vast. However, many studies are small pilot studies, and models often suffer from poor performance, limited reporting, and lack of external validation, which impede generalizability and clinical implementation. |
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| ISSN: | 2075-1729 |