Literature DB >> 8894381

Computer assisted diabetes care: a 6-year retrospective.

E D Lehmann1, T Deutsch.   

Abstract

Over the past 6 years we have designed a number of computer-based prototypes for the provision of therapeutic advice and the generation of glycaemic predictions in insulin-dependent (type 1) diabetic patients. In this paper we provide an overview of some of this work, and describe our experiences in trying to develop such methods for clinical use. We review, as an example, a model of the glucoregulatory system which has been developed for patient and medical staff education about type 1 diabetes mellitus, as well as possibly for therapeutic use. Using individualised parameter values the predictions of the model can be applied to generate 24-h simulations of patient blood glucose profiles. Previous preliminary retrospective validation work performed with this model has revealed a mean predictive accuracy for blood glucose simulations of approximately 2 mmol/l. Conceptual limitations of such modelling approaches are considered. We comment that such "mechanistic' models may lack the necessary sophistication and flexibility to represent the complexity of the human glucoregulatory system and the challenges it has to face. Although such methodologies may therefore not be suitable for safe and effective application in routine clinical practice, we conclude that the evolution of such a system for demonstration/educational purposes could have widespread clinical utility as an interactive teaching tool.

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Year:  1996        PMID: 8894381     DOI: 10.1016/0169-2607(96)01751-8

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


  4 in total

1.  Home blood glucose prediction: clinical feasibility and validation in islet cell transplantation candidates.

Authors:  A M Albisser; D Baidal; R Alejandro; C Ricordi
Journal:  Diabetologia       Date:  2005-06-03       Impact factor: 10.122

2.  Telemedicine and diabetes management: current challenges and future research directions.

Authors:  Riccardo Bellazzi
Journal:  J Diabetes Sci Technol       Date:  2008-01

3.  Dynamic Interactive Educational Diabetes Simulations Using the World Wide Web: An Experience of More Than 15 Years with AIDA Online.

Authors:  Eldon D Lehmann; Dennis K Dewolf; Christopher A Novotny; Karen Reed; Robert R Gotwals
Journal:  Int J Endocrinol       Date:  2014-01-06       Impact factor: 3.257

Review 4.  Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents.

Authors:  Amal Alqahtani
Journal:  Evid Based Complement Alternat Med       Date:  2022-04-25       Impact factor: 2.650

  4 in total

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