Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms-Reference-Cited by-同舟云学术

Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms

Published:2022-11-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering
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Author:

Chen Shengjia¹^ORCID,Gupta Nikunj²^ORCID,Galbraith Woodward B.³^ORCID,Shah Valay⁴^ORCID,Cirrone Jacopo⁵^ORCID

Affiliation:

1. Department of Radiology, New York University, Grossman School of Medicine, USA

2. New York University, Tandon School of Engineering, USA

3. New York University, Center for Data Science, USA

4. New York University, Courant Institute of Mathematical Sciences, USA

5. New York University, Center for Data Science, USA and Colton Center for Autoimmunity, New York University, Grossman School of Medicine, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3574198.3574221

Reference38 articles.

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2. Remission and active disease in rheumatoid arthritis: defining criteria for disease activity states;Aletaha Daniel;Arthritis & Rheumatism,2005

3. Factors predicting response to treatment in rheumatoid arthritis: the importance of disease duration;Anderson J;Arthritis & Rheumatism: Official Journal of the American College of Rheumatology,2000

4. The american rheumatism association 1987 revised criteria for the classification of rheumatoid arthritis

5. Convergent random forest predictor: Methodology for predicting drug response from genome-scale data applied to anti-TNF response

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