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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Автори:	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
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Elsevier 2023-12-01
Серія:	Osteoarthritis and Cartilage Open
Предмети:	Osteoarthritis Disease progression prediction Machine learning Patient selection for clinical trials Inclusion
Онлайн доступ:	http://www.sciencedirect.com/science/article/pii/S2665913123000730
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Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study

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