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AI-supported reasoning in physiotherapy

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Warianty tytułu
PL
Wnioskowanie w fizjoterapii wspierane sztuczną inteligencją
Języki publikacji
EN
Abstrakty
EN
Artificial intelligence (AI)-based clinical reasoning support systems in physiotherapy, and in particular data-driven (machine learning) systems, can be useful in making and reviewing decisions regarding functional diagnosis and formulating/maintaining/modifying a rehabilitation programme. The aim of this article is to explore the extent to which the opportunities offered by AI-based systems for clinical reasoning in physiotherapy have been exploited and where the potential for their further stimulated development lies.
PL
Systemy wspomagania wnioskowania klinicznego w fizjoterapii oparte na sztucznej inteligencji, a w szczególności na danych (uczenie maszynowe), mogą być przydatne w podejmowaniu i weryfikacji decyzji dotyczących diagnostyki funkcjonalnej ora formułowania/utrzymywania/modyfikowania programu rehabilitacji. Celem niniejszego artykułu jest zbadanie, w jakim stopniu możliwości oferowane przez systemy oparte na sztucznej inteligencji w zakresie rozumowania klinicznego w fizjoterapii zostały wykorzystane i gdzie leży potencjał ich dalszego stymulowanego rozwoju.
Rocznik
Strony
21--27
Opis fizyczny
Bibliogr. 43 poz., rys., tab.
Twórcy
  • Kazimierz Wielki University, Faculty of Computer Science Kopernika 1, 85-074 Bydgoszcz
  • Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Poland Department of Physiotherapy, Faculty of Health Sciences Jagiellońska 13-15, 85-087 Bydgoszcz
Bibliografia
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  • 2.Bilika P., Stefanouli V., Strimpakos N., Kapreli E.V., „Clinical reasoning using ChatGPT: Is it beyond credibility for physiotherapists use?”, Physiother Theory Pract. 2023, 11, 1-20. doi: 10.1080/09593985.2023.2291656.
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  • 24.Sandal L.F., Stochkendahl M.J., Svendsen M.J., Wood K., Øverås C.K., Nordstoga A.L., Villumsen M., Rasmussen C.D.N., Nicholl B., Cooper K., Kjaer P., Mair F.S., Sjøgaard G., Nilsen T.I.L., Hartvigsen J., Bach K., Mork P.J., Søgaard K.,„An app-delivered self-management program for people with low back pain: protocol for the selfBACK randomized controlled trial”, JMIR Res Protoc. 2019, 8(12), e14720. doi: 10.2196/14720.
  • 25.Sandal L.F., Bach K., Øverås C.K., Svendsen M.J., Dalager T., Stejnicher Drongstrup Jensen J., Kongsvold A., Nordstoga A.L., Bardal E.M., Ashikhmin I., Wood K., Rasmussen C.D.N., Stochkendahl M.J., Nicholl B.I., Wiratunga N., Cooper K., Hartvigsen J., Kjær P., Sjøgaard G., Nilsen T.I.L., Mair F.S., Søgaard K., Mork P.J..„Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: A self BACK randomized clinical trial”. JAMA Intern Med. 2021, 181(10), 1288-1296. doi: 10.1001/jamainternmed.2021.4097.
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  • 29.Rojek I., Jasiulewicz-Kaczmarek M., Piechowski M., Mikołajewski D., „An artificial intelligence approach for improving maintenance to supervise machine failures and support their repair”Applied Sciences 2023, 13 (8), 4971.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fa383aee-44a9-4b21-82eb-90bc1c743d36
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