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Artificial intelligence for disparities in knee pain assessment

Nature Medicine volume 27, pages 22–23 (2021)Cite this article

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An algorithm developed through machine learning on existing radiological data from diverse people has the potential to improve the diagnosis and management of knee pain from osteoarthritis and reduce racial disparities in the assessment of knee pain.

In the management of kneepain, particularly that from OA, the first line of treatment is physical therapy, weight loss, and pharmacological therapies with pain and anti-inflammatory medications. But when all else fails, surgical intervention, such as knee replacement, is recommended. The indications for surgery include not only pain but also function (pain that limits everyday activities) and quality of life. So it is not surprising that elective knee replacement is one of the fastest-growing elective surgical procedures in the USA and is appropriately a major cost center for the Centers for Medicare and Medicaid, which pays for majority of knee replacements in the country.

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Acknowledgements

S.A.I. is supported in part by a K24 Mid-Career Development Award from the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant K24AR05529).

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  1. Division of Healthcare Delivery Science & Innovation, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA

    Said A. Ibrahim

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  1. Said A. Ibrahim
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Correspondence to Said A. Ibrahim.

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Ibrahim, S.A. Artificial intelligence for disparities in knee pain assessment. Nat Med 27, 22–23 (2021). https://doi.org/10.1038/s41591-020-01196-3

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  • DOI: https://doi.org/10.1038/s41591-020-01196-3

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