Literature DB >> 2249420

Computer-aided systems in the management of type I diabetes: the application of a model-based strategy.

E Salzsieder1, G Albrecht, U Fischer, A Rutscher, U Thierbach.   

Abstract

One approach of improving metabolic control in type I diabetic patients is the application of computer-aided procedures aimed at supporting the decision on optimal therapeutic regimens. To accomplish this, a complex strategy was developed which in an individual patient permits (1) the evaluation of metabolic data by means of statistical and graphical methods, and (2) the prediction of the outcome in feedback and in non-feedback-controlled insulin therapy. The latter is realized by means of simulation, employing a structured model of the glucose-insulin control system where the model parameters can either be identified individually or be taken at random. The practical applicability was validated in C-peptide-negative type I diabetic patients who were on intensified insulin injection therapy. The comparison between theoretical predictions and daily glycaemic profiles measured by the patients under ambulatory conditions showed close correspondence which justifies the application of this method as a clinical decision support.

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Year:  1990        PMID: 2249420     DOI: 10.1016/0169-2607(90)90103-g

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  3 in total

1.  Telemedicine-based KADIS combined with CGMS has high potential for improving outpatient diabetes care.

Authors:  Eckhard Salzsieder; Petra Augstein; Lutz Vogt; Klaus-Dieter Kohnert; Peter Heinke; Ernst-Joachim Freyse; Abdel Azim Ahmed; Zakia Metwali; Iman Salman; Omer Attef
Journal:  J Diabetes Sci Technol       Date:  2007-07

2.  The Karlsburg Diabetes Management System: translation from research to eHealth application.

Authors:  Eckhard Salzsieder; Petra Augstein
Journal:  J Diabetes Sci Technol       Date:  2011-01-01

Review 3.  Artificial Intelligence in Decision Support Systems for Type 1 Diabetes.

Authors:  Nichole S Tyler; Peter G Jacobs
Journal:  Sensors (Basel)       Date:  2020-06-05       Impact factor: 3.576

  3 in total

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