2 citations · 2 across the 3 of their papers we have counts for
5 papers
Using Data Assimilation of Mechanistic Models to Estimate Glucose and Insulin Metabolism
Jami J. Mulgrave, Matthew E. Levine, David J. Albers +3
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 a…
The Parameter Houlihan: a solution to high-throughput identifiability indeterminacy for brutally ill-posed problems
DJ Albers, M Levine, L Mamykina +1
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, in…
Ensemble Kalman Methods With Constraints
David J. Albers, Paul-Adrien Blancquart, Matthew E. Levine +2
Ensemble Kalman methods constitute an increasingly important tool in both state and parameter estimation problems. Their popularity stems from the derivative-free nature of the met…
Methodological variations in lagged regression for detecting physiologic drug effects in EHR data
Matthew E. Levine, David J. Albers, George Hripcsak
We studied how lagged linear regression can be used to detect the physiologic effects of drugs from data in the electronic health record (EHR). We systematically examined the effec…
Offline and online data assimilation for real-time blood glucose forecasting in type 2 diabetes
Matthew E Levine, George Hripcsak, Lena Mamykina +2
We evaluate the benefits of combining different offline and online data assimilation methodologies to improve personalized blood glucose prediction with type 2 diabetes self-monito…