JSM Preliminary Online Program
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Activity Number: 423
Type: Contributed
Date/Time: Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #304962
Title: Subclassifying Type 2 Diabetes by Combining Nonlinear Dynamic Modeling and Multivariate Classification Methods
Author(s): Lucas Beverlin*+ and Derrick Rollins and Nisarg Vyas and Gregory Welk and Warren Franke
Companies: Iowa State University and Iowa State University and BodyMedia, Inc. and Iowa State University and Iowa State University
Address: , , ,
Keywords: multivariate analysis ; diabetes ; dynamics ; nonlinear modeling
Abstract:

Type II diabetes is an affliction reaching pandemic proportions in the United States. This disease affects each person differently, and thus is difficult to treat. To help people with diabetes better control their glucose levels, we monitored their blood glucose, physical activity, physiological activity and food under free-living conditions for four weeks. From the collected data, we will develop a nonlinear dynamic model of their glucose based on their activity and food. Then we will use multivariate statistical techniques as well as these fitted models in order to classify subjects into groups that can control their glucose in a similar manner.

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Revised September, 2008