Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study

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 enrichment, we developed a machine learning recruitmen...

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Autori principali:	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
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2023-12-01
Serie:	Osteoarthritis and Cartilage Open
Soggetti:	Osteoarthritis Disease progression prediction Machine learning Patient selection for clinical trials Inclusion
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2665913123000730
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