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Atomatic adjustment of Basal insulin infusion rates in type 1 diabetes using run-to-run control and case-based reasoning
File | Description | Size | Format | |
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1-AID_2017_paper_10.pdf | Accepted version | 516.14 kB | Adobe PDF | View/Open |
Title: | Atomatic adjustment of Basal insulin infusion rates in type 1 diabetes using run-to-run control and case-based reasoning |
Authors: | 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. |
Issue 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: | Electrical and Electronic Engineering Faculty of Engineering |