  Motivation: There is a growing need to integrate mechanistic models of
biological processes with computational methods in healthcare in order to
improve prediction. We apply data assimilation in the context of Type 2
diabetes to understand parameters associated with the disease.
  Results: The data assimilation method captures how well patients improve
glucose tolerance after their surgery. Data assimilation has the potential to
improve phenotyping in Type 2 diabetes.
