Using reinforcement learning to identify high-risk states and treatments in healthcare

Figure at the start of a maze showing several paths. Four paths include a medical dead-end, and each stop before reaching the end. Only one path does not include a medical-dead end, and this one goes clear through to the end.

As the pandemic overburdens medical facilities and clinicians become increasingly overworked, the ability to make quick decisions on providing the best possible treatment is even more critical. In urgent health situations, such decisions can mean life or death. However, certain treatment protocols can pose a considerable risk

 

 

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