Nature Communications (May 2021)

Health improvement framework for actionable treatment planning using a surrogate Bayesian model

  • Kazuki Nakamura,
  • Ryosuke Kojima,
  • Eiichiro Uchino,
  • Koh Ono,
  • Motoko Yanagita,
  • Koichi Murashita,
  • Ken Itoh,
  • Shigeyuki Nakaji,
  • Yasushi Okuno

DOI
https://doi.org/10.1038/s41467-021-23319-1
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 15

Abstract

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Clinical decision-making regarding treatments based on personal characteristics leads to effective health improvements. Here, the authors introduce a modeling framework to evaluate the actionability of treatment pathways.