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Machine learning model for identifying important clinical features for predicting remission in patients with rheumatoid arthritis treated with biologics.

Bon San KooSeongho EunKichul ShinHyemin YoonChaelin HongDo-Hoon KimSeokchan HongYong-Gil KimChang-Keun LeeBin YooJi-Seon Oh
Published in: Arthritis research & therapy (2021)
Our proposed machine learning model successfully identified clinical features that were predictive of remission in each of the bDMARDs. This approach may be useful for improving treatment outcomes by identifying clinical information related to remissions in patients with rheumatoid arthritis.
Keyphrases
  • machine learning
  • disease activity
  • artificial intelligence
  • big data
  • healthcare
  • health information
  • systemic lupus erythematosus
  • newly diagnosed