Machine learning using genetic and clinical data identifies a signature that robustly predicts methotrexate response in rheumatoid arthritis

Machine learning using genetic and clinical data identifies a signature that robustly predicts methotrexate response in rheumatoid arthritis

10.1093/rheumatology/keac032

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Bibliographic Details
Main Authors: Lim, Lee Jin, Lim, Ashley JW, BRANDON OOI NICK SERN, Tan, Justina Wei Lynn, Koh, Ee Tzun, Group, Ttsh Rheumatoid Arthritis Study, Chong, Samuel S, Khor, Chiea Chuen, Tucker-Kellogg, Lisa, Lee, Caroline G, Leong, Khai Pang
Other Authors: BIOCHEMISTRY
Format: Article
Language:English
Published: OXFORD UNIV PRESS 2022
Subjects:
Science & Technology
Life Sciences & Biomedicine
Rheumatology
rheumatoid arthritis
methotrexate
genetic polymorphism
machine learning
feature selection
FUNCTIONAL ANNOTATION
RHEUMATOLOGY/EUROPEAN LEAGUE
AMERICAN-COLLEGE
DISEASE-ACTIVITY
SCORES
PHARMACOGENETICS
CLASSIFICATION
COMBINATION
SNPNEXUS
CRITERIA
Online Access:https://scholarbank.nus.edu.sg/handle/10635/226870
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Institution: National University of Singapore
Language: English

Internet

https://scholarbank.nus.edu.sg/handle/10635/226870

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