Learning Evolving Patient Risk Processes for C . Diff Colonization

  title={Learning Evolving Patient Risk Processes for C . Diff Colonization},
  author={Jenna Wiens and Eric Horvitz},
Predictions of adverse events during hospitalizations can be used in programs aimed at improving patient outcomes. A patient’s risk for adverse events may be biased by temporal processes influenced by diagnostic and therapeutic activities, as well as by the overall evolution of the patient’s pathophysiology over time. Representing and reasoning about temporal process promises to enhance the accuracy of inferences about risk. However, understanding temporal influences is challenging for a number… CONTINUE READING
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