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arXiv · 2003.06541

Using Data Assimilation of Mechanistic Models to Estimate Glucose and Insulin Metabolism

Jami J. Mulgrave·Matthew E. Levine·David J. Albers·Joon Ha·Arthur Sherman·George Hripcsak
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Abstract

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.

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Jami J. Mulgrave, Matthew E. Levine, David J. Albers, Joon Ha, Arthur Sherman, George Hripcsak. 2020-03-14. Using Data Assimilation of Mechanistic Models to Estimate Glucose and Insulin Metabolism. https://arxiv.org/abs/2003.06541

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