Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Pawel Widera"'
Autor:
Margreet Kloppenburg, Ida K Haugen, Paco M J Welsing, Francisco J Blanco, Christoph Ladel, Jaume Bacardit, Floris Lafeber, Eefje Martine van Helvoort, Simon Mastbergen, Pawel Widera
Publikováno v:
RMD Open, Vol 7, Iss 3 (2021)
Objectives To describe the relations between baseline clinical characteristics of the Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) participants and their predicted probabilities for knee osteoarthritis (OA)
Externí odkaz:
https://doaj.org/article/0fbbbe26c75542cdb1c4d3fdd30e162f
Autor:
Eefje M van Helvoort, Mylène P Jansen, Anne C A Marijnissen, Margreet Kloppenburg, Francisco J Blanco, Ida K Haugen, Francis Berenbaum, Anne-Christine C Bay-Jensen, Christoph Ladel, Agnes Lalande, Jonathan Larkin, John Loughlin, Ali Mobasheri, Harrie H Weinans, Pawel Widera, Jaume Bacardit, Paco M J Welsing, Floris P J G Lafeber
Publikováno v:
Rheumatology. OXFORD UNIV PRESS
Rheumatology
Rheumatology
Objectives The IMI-APPROACH knee osteoarthritis study used machine learning (ML) to predict structural and/or pain progression, expressed by a structural (S) and pain (P) predicted-progression score, to select patients from existing cohorts. This stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4bb032e1f5cc63fcdd5bae49f3fdd88a
https://doi.org/10.1093/rheumatology/keac292
https://doi.org/10.1093/rheumatology/keac292
Autor:
Paweł Widera, Paco M.J. Welsing, Samuel O. Danso, Sjaak Peelen, Margreet Kloppenburg, Marieke Loef, Anne C. Marijnissen, Eefje M. van Helvoort, Francisco J. Blanco, Joana Magalhães, Francis Berenbaum, Ida K. Haugen, Anne-Christine Bay-Jensen, Ali Mobasheri, Christoph Ladel, John Loughlin, Floris P.J.G. Lafeber, Agnès Lalande, Jonathan Larkin, Harrie Weinans, Jaume Bacardit
Publikováno v:
Osteoarthritis and Cartilage Open, Vol 5, Iss 4, Pp 100406- (2023)
Objectives: To efficiently assess the disease-modifying potential of new osteoarthritis treatments, clinical trials need progression-enriched patient populations. To assess whether the application of machine learning results in patient selection enri
Externí odkaz:
https://doaj.org/article/55e22c14dfcd491ebe747a57d5aa24d7