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

Rheumatology (Oxford, England) - 6 Oct 2022

Lim Lee Jin, Lim Ashley J W, Ooi Brandon N S, Tan Justina Wei Lynn, Koh Ee Tzun, Chong Samuel S, Khor Chiea Chuen, Tucker-Kellogg Lisa, Lee Caroline G, Leong Khai Pang

Abstract excerpt

OBJECTIVE: To develop a hypothesis-free model that best predicts response to MTX drug in RA patients utilizing biologically meaningful genetic feature selection of potentially functional single nucleotide polymorphisms (pfSNPs) through robust machine learning (ML) feature selection methods. METHODS: MTX-treated RA patients with known response were divided in a 4:1 ratio into training and test sets. From the...

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PMID: 35094058
DOI: 10.1093/rheumatology/keac032

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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