Machine learning to identify immune-related biomarkers of rheumatoid arthritis based on WGCNA network
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Medicine,Rheumatology
Link
https://link.springer.com/content/pdf/10.1007/s10067-021-05960-9.pdf
Reference44 articles.
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3. Smolen JS, Aletaha D, Barton A, Burmester GR, Emery P, Firestein GS, Kavanaugh A, McInnes IB, Solomon DH, Strand V, Yamamoto K (2018) Rheumatoid arthritis. Nature reviews. Dis Primers 418001. https://doi.org/10.1038/nrdp.2018.1
4. Courvoisier DS, Chatzidionysiou K, Mongin D, Lauper K, Mariette X, Morel J, Gottenberg JE, Bergstra SA, Suarez MP, Codreanu C, Kvien TK, Santos MJ, Pavelka K, Hetland ML, Askling J, Turesson C, Kubo S, Tanaka Y, Iannone F, Choquette D, Nordström DC, Rotar Z, Lukina G, Gabay C, Van Vollenhoven R, Finckh A (2021) The impact of seropositivity on the effectiveness of biologic anti-rheumatic agents: results from a collaboration of 16 registries. Rheumatology (Oxford) 60(2):820–828. https://doi.org/10.1093/rheumatology/keaa393
5. Laborde CM, Castro-Santos P, Díaz-Peña R (2020) Contribution of multiplex immunoassays to rheumatoid arthritis management: from biomarker discovery to personalized medicine. J Personal Med 10(4). https://doi.org/10.3390/jpm10040202
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