Title
Synthesis Of Insulin Pump Controllers From Safety Specifications Using Bayesian Model Validation
Keywords
Artificial pancreas; Automated synthesis; Bayesian statistical model checking; Computational systems biology; Diabetes; Parameter synthesis
Abstract
Insulin pump controllers seek to alleviate the chronic suffering caused by diabetes that affects over 6% of the world population. The design of control laws for insulin pump controllers has been well studied. However, the parameters involved in the control law are difficult to synthesize. Traditionally, ad hoc approaches using animal models and random sampling have been used to construct these parameters. We suggest a synthesis algorithm that uses Bayesian statistical model validation to reduce the number of simulations needed. We apply this algorithm to the problem of insulin pump controller synthesis using in silico simulation of the glucose-insulin metabolism model. Copyright © 2012 Inderscience Enterprises Ltd.
Publication Date
1-1-2012
Publication Title
International Journal of Bioinformatics Research and Applications
Volume
8
Issue
3-4
Number of Pages
263-285
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1504/IJBRA.2012.048964
Copyright Status
Unknown
Socpus ID
84866236069 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84866236069
STARS Citation
Jha, Sumit Kumar; Dutta, Raj Gautam; Langmead, Christopher J.; Jha, Susmit; and Sassano, Emily, "Synthesis Of Insulin Pump Controllers From Safety Specifications Using Bayesian Model Validation" (2012). Scopus Export 2010-2014. 5506.
https://stars.library.ucf.edu/scopus2010/5506