In this paper, we build a new, simple, and interpretable mathematical model to describe the human glucose-insulin system. Our goal is the robust control of the blood-glucose (BG) level of individuals to a desired healthy range, by means of adjusting …
One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, instead of a set of functions, such as neural networks. Such regressions …
We evaluate the benefits of combining different offline and online data assimilation methodologies to improve personalized blood glucose prediction with type 2 diabetes self-monitoring data. We collect self-monitoring data (nutritional reports and …