Academic Paper

Reinforcement Learning for Precision Oncology

September, 2021

Summary

The accelerating merger of information technology and cancer research heralds the advent of novel methods and models for clinical decision making in oncology. Reinforcement learning—as one of the major subspecialties in machine learning—holds the potential for the development of high-performance decision support tools. However, many recent studies of reinforcement learning in oncology suffer from common shortcomings and pitfalls that need to be addressed for the development of safe, interpretable and reliable algorithms for future clinical practice.

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