Intelligent personalized medical decision support systems for the management of diabetes mellitus

Abstract

The scope of the present thesis is the design, development and evaluation of intelligent medical decision support systems, aiming at optimizing the treatment of patients with Diabetes Mellitus (DM). Specifically, within the framework of the present thesis, several methods have been developed for the analysis and processing of data related to medical electronic health records, laboratory measurements and continuous glucose and insulin records, towards the design and the development of: i) an intelligent Insulin Infusion Advisory System (IIAS), able to provide real time estimations of the appropriate insulin infusion rates for type 1 DM patients using continuous glucose monitors and insulin pumps (Artificial Pancreas), in order to maintain glucose levels within the physiological range, and ii) models for the risk assessment of long-term complications of Type I and Type II DM, focusing on diabetic retinopathy. In the first part of this study, a simulation model of the glucose - insulin me ...
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DOI
10.12681/eadd/24790
Handle URL
http://hdl.handle.net/10442/hedi/24790
ND
24790
Alternative title
Ευφυή συστήματα υποστήριξης εξατομικευμένων ιατρικών αποφάσεων για τη διαχείριση του σακχαρώδους διαβήτη
Author
Zarkogianni, Konstantia (Father's name: Christos)
Date
2011
Degree Grantor
National Technical University of Athens (NTUA)
Committee members
Νικήτα Κωνσταντίνα
Ουζουνόγλου Νικόλαος
Κουτσούρης Δημήτριος
Σταφυλοπάτης Ανδρέας
Ματσόπουλος Γεώργιος
Φωτιάδης Δημήτριος
Μπαρτσόκας Χρήστος
Discipline
Engineering and TechnologyElectrical Engineering, Electronic Engineering, Information Engineering
Keywords
Diabetes mellitus; Glucose; Insulin; Retinopathy; Artificial pancreas; Subcutaneous route; Model predictive control; Autotuning controller; Compartmental models; Recurrent neural networks
Country
Greece
Language
Greek
Description
xviii, 182 σ., im.
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