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Peripheral blood DNA methylation-based machine learning models for prediction of knee osteoarthritis progression: biospecimens and data from the Osteoarthritis Initiative and Johnston County Osteoarthritis Project

CITE Title : Peripheral blood DNA methylation-based machine learning models for prediction of knee osteoarthritis progression: biospecimens and data from the Osteoarthritis Initiative and Johnston County Osteoarthritis Project Personal Author(s) : Dunn, Christopher M.;Sturdy, Cassandra;Velasco, Cassandra;Schlupp, Leoni;Prinz, Emmaline;Izda, Vladislav;Arbeeva, Liubov;Golightly, Yvonne M.;Nelson, Amanda E.;Jeffries, Matlock A.; Published Date : 1 2023 Source : Arthritis Rheumatol. 75(1):28-40 URL : https://stacks.cdc.gov/view/cdc/140160 Dunn, Christopher M. et al. (2023). Peripheral blood DNA methylation-based machine learning models for prediction of knee osteoarthritis progression: biospecimens and data from the Osteoarthritis Initiative and Johnston County Osteoarthritis Project. 75(1). Dunn, Christopher M. et al. "Peripheral blood DNA methylation-based machine learning models for prediction of knee osteoarthritis progression: biospecimens and data from the Osteoarthritis Initiative and Johnston County Osteoarthritis Project" 75, no. 1 (2023) Dunn, Christopher M. et al. "Peripheral blood DNA methylation-based machine learning models for prediction of knee osteoarthritis progression: biospecimens and data from the Osteoarthritis Initiative and Johnston County Osteoarthritis Project" vol. 75, no. 1, 2023 Export RIS Citation Information.

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Dunn, Christopher M.

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Sturdy, Cassandra

1 2023 | Arthritis Rheumatol. 75(1):28-40

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Objective:The lack of accurate biomarkers to predict knee osteoarthritis (OA) progression is a key unmet need in the OA field. The objective of this s...

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