Corpus ID: 219176547

Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology

@article{Maier2020ReinforcementLA,
  title={Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology},
  author={Corinna Maier and Niklas Hartung and C. Kloft and W. Huisinga and Jana de Wiljes},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.01061}
}
  • Corinna Maier, Niklas Hartung, +2 authors Jana de Wiljes
  • Published 2020
  • Computer Science, Mathematics, Biology
  • ArXiv
  • Model-informed precision dosing (MIPD) using therapeutic drug/biomarker monitoring offers the opportunity to significantly improve the efficacy and safety of drug therapies. Current strategies comprise model-informed dosing tables or are based on maximum a-posteriori estimates. These approaches, however, lack a quantification of uncertainty and/or consider only part of the available patient-specific information. We propose three novel approaches for MIPD employing Bayesian data assimilation (DA… CONTINUE READING

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