Literature DB >> 26862136

Case-Based Reasoning for Insulin Bolus Advice.

Peter Pesl1, Pau Herrero1, Monika Reddy2, Nick Oliver2, Desmond G Johnston2, Christofer Toumazou1, Pantelis Georgiou1.   

Abstract

BACKGROUND: Insulin bolus calculators assist people with Type 1 diabetes (T1D) to calculate the amount of insulin required for meals to achieve optimal glucose levels but lack adaptability and personalization. We have proposed enhancing bolus calculators by the means of case-based reasoning (CBR), an established problem-solving methodology, by individualizing and optimizing insulin therapy for various meal situations. CBR learns from experiences of past similar meals, which are described in cases through a set of parameters (eg, time of meal, alcohol, exercise). This work discusses the selection, representation and effect of case parameters used for a CBR-based Advanced Bolus Calculator for Diabetes (ABC4D).
METHODS: We analyzed the usage and effect of selected parameters during a pilot study (n = 10), where participants used ABC4D for 6 weeks. Retrospectively, we evaluated the effect of glucose rate of change before the meal on the glycemic excursion. Feedback from study participants about the choice of parameters was obtained through a nonvalidated questionnaire.
RESULTS: Exercise and alcohol were the most frequently used parameters, which was congruent with the feedback from study participants, who found these parameters most useful. Furthermore, cases including either exercise or alcohol as parameter showed a trend in reduction of insulin at the end of the study. A significant difference ( P < .01) was found in glycemic outcomes for meals where glucose rate of change was rising compared to stable rate of change.
CONCLUSIONS: Results from the 6-week study indicate the potential benefit of including parameters exercise, alcohol and glucose-rate of change for insulin dosing decision support.

Entities:  

Keywords:  bolus calculator; case parameters; case-based-reasoning; decision support; diabetes management; insulin dosing algorithm

Mesh:

Substances:

Year:  2016        PMID: 26862136      PMCID: PMC5375057          DOI: 10.1177/1932296816629986

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


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Journal:  Diabetes Technol Ther       Date:  2008-12       Impact factor: 6.118

8.  Method for automatic adjustment of an insulin bolus calculator: in silico robustness evaluation under intra-day variability.

Authors:  Pau Herrero; Peter Pesl; Jorge Bondia; Monika Reddy; Nick Oliver; Pantelis Georgiou; Christofer Toumazou
Journal:  Comput Methods Programs Biomed       Date:  2015-02-16       Impact factor: 5.428

9.  Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning.

Authors:  Pau Herrero; Peter Pesl; Monika Reddy; Nick Oliver; Pantelis Georgiou; Christofer Toumazou
Journal:  IEEE J Biomed Health Inform       Date:  2015-05       Impact factor: 5.772

10.  An Advanced Bolus Calculator for Type 1 Diabetes: System Architecture and Usability Results.

Authors:  Peter Pesl; Pau Herrero; Monika Reddy; Maria Xenou; Nick Oliver; Desmond Johnston; Christofer Toumazou; Pantelis Georgiou
Journal:  IEEE J Biomed Health Inform       Date:  2015-08-03       Impact factor: 5.772

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  4 in total

1.  Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra-day variability.

Authors:  Pau Herrero; Jorge Bondia; Oloruntoba Adewuyi; Peter Pesl; Mohamed El-Sharkawy; Monika Reddy; Chris Toumazou; Nick Oliver; Pantelis Georgiou
Journal:  Comput Methods Programs Biomed       Date:  2017-06-01       Impact factor: 5.428

2.  Using Case-Based Reasoning in a Learning System: A Prototype of a Pedagogical Nurse Tool for Evidence-Based Diabetic Foot Ulcer Care.

Authors:  Clara Bender; Simon Lebech Cichosz; Alberto Malovini; Riccardo Bellazzi; Louise Pape-Haugaard; Ole Hejlesen
Journal:  J Diabetes Sci Technol       Date:  2021-02-15

Review 3.  Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

Authors:  Ivan Contreras; Josep Vehi
Journal:  J Med Internet Res       Date:  2018-05-30       Impact factor: 5.428

Review 4.  Application of Artificial Intelligence in Diabetes Education and Management: Present Status and Promising Prospect.

Authors:  Juan Li; Jin Huang; Lanbo Zheng; Xia Li
Journal:  Front Public Health       Date:  2020-05-29
  4 in total

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