Learning Optimal Treatment Strategies for Sepsis Using Offline Reinforcement Learning in Continuous Space. (arXiv:2206.11190v1 [cs.LG])

Web: http://arxiv.org/abs/2206.11190

Sepsis is a leading cause of death in the ICU. It is a disease requiring
complex interventions in a short period of time, but its optimal treatment
strategy remains uncertain. Evidence suggests that the practices of currently
used treatment strategies are problematic and may cause harm to patients. To
address this decision problem, we propose a new medical decision model based on
historical data to help clinicians recommend the best reference option for
real-time treatment. Our model combines offline reinforcement …

arxiv learning lg reinforcement reinforcement learning space strategies treatment