A Reinforcement Learning-Based Approach for the Risk Management of e-Health Environments: A Case Study

Modern medical software systems are often classified as medical devices and governed by regulations which require stringent risk safety activities to be implemented to minimize the occurrence of risky events. This paper proposes a Reinforcement Learning (RL based approach for training a software agent for risk management of medical software systems. The goal of the RL agent is to avoid that a patient enters in dangerous and undesirable states. At the same time, the agent must be able to reach on a safe state or an exit in a minimum interval of time.