Applying process control and machine learning to develop effective dynamic decision strategies [presentation] Presentation uri icon
  • Dynamic decision making (DDM) requires an agent to make a series of pathdependent, time-critical decisions in environments that change as a result of the agent’s actions as well as autonomously. We model DDM as a process control problem using a general-purpose “measure-intervene-iterate” framework and propose a machine learning approach to improving decision strategies. We present results from applying the technique in a simulation of an important healthcare DDM problem, namely diabetes care.

  • participant
  • Adomavicius, G.   Presenter  
  • Elidrisi, M. A.   Presenter  
  • Johnson, P. E.   Presenter  
  • Meyer, G.   Presenter  
  • O'Connor, Patrick J., MD   Presenter  
  • Rush, William A., PhD   Presenter  
  • Sperl-Hillen, JoAnn M., MD   Presenter  
  • Research
  • Decision Making
  • Diabetes
  • Informatics