Atomatic adjustment of Basal insulin infusion rates in type 1 diabetes using run-to-run control and case-based reasoning

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Title: Atomatic adjustment of Basal insulin infusion rates in type 1 diabetes using run-to-run control and case-based reasoning
Author(s): Herrero Vinas, P
Pesl, P
Reddy, M
Oliver, N
Georgiou, P
Item Type: Conference Paper
Abstract: People with type 1 diabetes mellitus rely on a basal-bolus insulin regimen to roughly emulate how a non-diabetic person’s body delivers insulin. Adjusting such regime is a challenging process usually conducted by an expert clinical. Despite several guidelines exist for such purpose, they are usually impractical and fall short in achieving optimal glycemic outcomes. Therefore, there is a need for more automated and efficient strategies to adjust such regime. This paper presents, and in silico validates, a novel technique to automatically adapt the basal insulin profile of a person with person with type 1 diabetes. The presented technique, which is based on Run-to-Run control and Case-Based Reasoning, overcomes some of the limitations of previously proposed approaches and has been proved to be robust in front of realistic intra-day variability. Over a period of 5 weeks on 10 virtual adult subjects, a significant reduction on the percentage of time in hyperglycemia (<70mg/dl) (from 14.3±5.6 to 1.6±1.7, p< 0.01), without a significant increase on the percentage of time in hypoglycemia (>180mg/dl) (from 10.2±5.9 to 1.6±1.7, p=0.1), was achieved.
Publication Date: 24-Jun-2017
Date of Acceptance: 24-May-2017
URI: http://hdl.handle.net/10044/1/55731
Journal / Book Title: 2nd Workshop on Artificial Intelligence for Diabetes (AID2017)
Copyright Statement: © 2017 The Author(s)
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
National Institute for Health Research
National Institute for Health Research
Commission of the European Communities
Funder's Grant Number: EP/M027007/1
EP/M027007/1
II-LA-0214-20008
II-LA-0214-20008
689810
Conference Name: Artificial Intelligence in Medicine
Publication Status: Published
Start Date: 2017-06-24
Conference Place: Vienna, Austria
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



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