• Curr Pain Headache Rep · Aug 2024

    Review

    The Role and Applications of Artificial Intelligence in the Treatment of Chronic Pain.

    • Tiffany A Meier, Mohammad S Refahi, Gavin Hearne, Daniele S Restifo, Ricardo Munoz-Acuna, Gail L Rosen, and Stephen Woloszynek.
    • South Shore Medical Center, Norwell, MA, USA.
    • Curr Pain Headache Rep. 2024 Aug 1; 28 (8): 769784769-784.

    Purpose Of ReviewThis review aims to explore the interface between artificial intelligence (AI) and chronic pain, seeking to identify areas of focus for enhancing current treatments and yielding novel therapies.Recent FindingsIn the United States, the prevalence of chronic pain is estimated to be upwards of 40%. Its impact extends to increased healthcare costs, reduced economic productivity, and strain on healthcare resources. Addressing this condition is particularly challenging due to its complexity and the significant variability in how patients respond to treatment. Current options often struggle to provide long-term relief, with their benefits rarely outweighing the risks, such as dependency or other side effects. Currently, AI has impacted four key areas of chronic pain treatment and research: (1) predicting outcomes based on clinical information; (2) extracting features from text, specifically clinical notes; (3) modeling 'omic data to identify meaningful patient subgroups with potential for personalized treatments and improved understanding of disease processes; and (4) disentangling complex neuronal signals responsible for pain, which current therapies attempt to modulate. As AI advances, leveraging state-of-the-art architectures will be essential for improving chronic pain treatment. Current efforts aim to extract meaningful representations from complex data, paving the way for personalized medicine. The identification of unique patient subgroups should reveal targets for tailored chronic pain treatments. Moreover, enhancing current treatment approaches is achievable by gaining a more profound understanding of patient physiology and responses. This can be realized by leveraging AI on the increasing volume of data linked to chronic pain.© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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