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Comparison of multivariate linear regression and a machine learning algorithm developed for prediction of precision warfarin dosing in a Korean population.

Van Lam NguyenHoang Dat NguyenYong-Soon ChoHo-Sook KimIl-Yong HanDae-Kyeong KimSangzin AhnJae-Gook Shin
Published in: Journal of thrombosis and haemostasis : JTH (2021)
This study shows that our LR and GMB models are satisfactory to predict warfarin dose in our dataset. Both models showed similar performance and feature contribution characteristics. LR may be the appropriate model due to its simplicity and interpretability.
Keyphrases
  • machine learning
  • atrial fibrillation
  • deep learning
  • venous thromboembolism
  • direct oral anticoagulants
  • artificial intelligence
  • big data
  • oral anticoagulants
  • neural network
  • data analysis