Learning Stroke Treatment Progression Models for an MDP Clinical Decision Support System

  title={Learning Stroke Treatment Progression Models for an MDP Clinical Decision Support System},
  author={Dan C. Coroian and Kris Hauser},
This paper describes a clinical decision support framework in multi-step health care domains that can dynamically recommend optimal treatment plans with respect to both patient outcomes and expected treatment cost. Our system uses a modified POMDP framework in which hidden states are not explicitly modeled, but rather, probabilistic models for predicting future observables given observation and action histories are learned directly from electronic health record (EHR) data. High quality… CONTINUE READING
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