Показати скорочений опис матеріалу

dc.contributor.author Mourad, R.
dc.contributor.author Kolisnyk, S.
dc.contributor.author Kim, J.
dc.contributor.author Rusakov, A.
dc.date.accessioned 2025-03-22T16:18:16Z
dc.date.available 2025-03-22T16:18:16Z
dc.date.issued 2022
dc.identifier.citation 6) Performance of artificial intelligence in determining candidacy for lumbar stenosis surgery : The Journal of the International Society of Physical and Rehabilitation Medicine / Mourad, R., Kolisnyk, S., Kim, J., Rusakov, A., & Lebl, D. ; 5(Supplement 2), S5368. Wolters Kluwer - Medknow, 2022. – 1 p. uk_UA
dc.identifier.uri https://dspace.vnmu.edu.ua/123456789/8702
dc.description.abstract Lumbar spinal stenosis (LSS) is a condition affecting 250,000 adults in the US each year. LSS is associated with a huge economic burden, with US$ 40 billion spent on surgery each year, and a relatively high rate of clinical failure postoperatively. We hypothesized that artificial intelligence (AI) provides comparable performance to a panel of spine experts uk_UA
dc.language.iso en uk_UA
dc.title Performance of artificial intelligence in determining candidacy for lumbar stenosis surgery uk_UA
dc.type Article uk_UA


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Показати скорочений опис матеріалу