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Proceedings ArticleDOI

Decision support in diabetes management for optimal glycaemic control by insulin administration

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TLDR
An expert system to assist diabetic patient management by blood glycose monitoring through insulin administration is described, which incorporates decision making situations of patient management in Greece where diet, life style and administration of insulin differ from Northern European countries.
Abstract
Optimal glycaemic control is achieved by diet manipulation and insulin administration. The potential benefits in using decision support systems for diabetic patient management are the cost saving they provide in terms of expensive man hours of verbal instruction by medical experts and the support in terms of objective and consistent decision making by the experts. This paper describes an expert system to assist diabetic patient management by blood glycose monitoring through insulin administration. The system incorporates decision making situations of patient management in Greece where diet, life style and administration of insulin differ from Northern European countries. This application is carried out at the First Propaedeutic Medical Clinic, the Ahepa General Hospital of Thessaloniki, Greece. >

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A Neural Network Approach in Diabetes Management by Insulin Administration

TL;DR: This paper investigates the application of a neural network approach for the development of a prototype system for knowledge classification in this domain, and finds it applicable to this particular problem, classifing correctly 92% of the testing cases.
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Clinical evaluation of the DIABETES expert system for decision support by multiple regimen insulin dose adjustment

TL;DR: A performance evaluation of the DIABETES rule-based expert system prototype for clinical decision making, which facilitates multiple insulin regimen and dose adjustment of insulin dependent Type I or II diabetic patients, shows potential benefits in terms of cost saving and education and training of medical personnel.
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Decision support for insulin regime prescription based on a neural-network approach.

TL;DR: A system supporting the decision making of medical personnel with respect to the specification of insulin regimes, based on a neural network methodology, which dramatically reduces training time and guarantees the monotonically decreasing nature of the error function.
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Non Invasive Blood Glucose Detection along with an Assistive Diabetes Monitoring App

TL;DR: The paper involves the design of a noninvasive glucose level detector using the Near Infrared (NIR) Spectroscopy concept and a smart device which is interfaced to an android device via Bluetooth to a monitoring android application which assist in keeping track of the glucose level.
References
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TL;DR: The effect of different foods on the blood glucose levels was fed individually to groups of 5 to 10 healthy fasting volunteers, and a significant negative relationship was seen between fat and protein and postprandial glucose rise but not with fiber or sugar content.
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The use of the glycemic index in predicting the blood glucose response to mixed meals.

TL;DR: How data may be analyzed to make use of the GI values of individual foods to predict the GI of mixed meals is demonstrated.
Journal ArticleDOI

A physiological model of glucose-insulin interaction in type 1 diabetes mellitus.

TL;DR: A clinical model of glucose-insulin interaction in insulin-dependent diabetes mellitus has been developed for patient and medical staff education and the possible use of the model as a tool for automated insulin dosage adjustment is explored.
Journal ArticleDOI

Dietary analysis with the aid of a microcomputer

TL;DR: The design, development, implementation and use of a microcomputer software package to assist hospital and other dietitians with a variety of arithmetical tasks relating to analysis of their patients' diets in terms of nutrient content are described.
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