Complex Machine-Learning Algorithms and Multivariable Logistic Regression on Par in the Prediction of Insufficient Clinical Response to Methotrexate in Rheumatoid Arthritis

Complex Machine-Learning Algorithms and Multivariable Logistic Regression on Par in the Prediction of Insufficient Clinical Response to Methotrexate in Rheumatoid Arthritis

The goals of this study were to examine whether machine-learning algorithms outperform multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to investigate whether the...

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Bibliographic Details
Main Authors: Helen R. Gosselt, Maxime M. A. Verhoeven, Maja Bulatović-Ćalasan, Paco M. Welsing, Maurits C. F. J. de Rotte, Johanna M. W. Hazes, Floris P. J. G. Lafeber, Mark Hoogendoorn, Robert de Jonge
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Journal of Personalized Medicine
Subjects:
arthritis
rheumatoid
methotrexate
outcome assessment
healthcare
therapeutics
Online Access:https://www.mdpi.com/2075-4426/11/1/44

Internet

https://www.mdpi.com/2075-4426/11/1/44

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