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 |