Using artificial neural networks models for predicting pancreas behavior
Other Title(s)
استخدام الشبكات العصوبنية في التنبؤ في سلوك البنكرياس
Dissertant
Thesis advisor
University
Philadelphia University
Faculty
Faculty of Information Technology
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2008
English Abstract
-Artificial Neural Network (ANN) is currently a 'hot' research area in medicine and this work is based on predicting the behavior of an organ of a human body called pancreas by using neural networks.
Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques.
Their ability to learn by example makes them very flexible and powerful.
So we have data set from 102 of three different groups of subjects.
From data set examples, neural networks were learned by using two algorithms, Radial Basis Function (RBF) and General regression Neural Network (GRNN).
After learning, a simulation (testing) for learned data has been made and a comparison between both algorithms has been done subject to the learning performance.
Furthermore a comparison between RBF and GRNN algorithms was done based on the ability of both networks to generalize input data not seen before.
All simulations were made by MATLAB 7 neural network toolbox and the results showed that RBF and GRNN are good function approximators.
It was noticeable that RBF and GRNN were fast training algorithms even GRNN was faster.
It was apparent that neural network was a good choice for predicting a behavior of nonlinear and complex systems such as pancreas.
Also the results showed that the performance of RBF in learning was better than GRNN, and the ability of GRNN in generalization or testing was better than RBF.
Main Subjects
Topics
No. of Pages
76
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : A literature review of neural network algorithms used for regulating glucose level.
Chapter Three : The pancreas and its endocrine system.
Chapter Four : Artificial neural networks algorithms for function approximation.
Chapter Five : Design and implementation.
Chapter Six : Results.
Chapter Seven : Conclusions and future work.
References.
American Psychological Association (APA)
Abid, Bassam Abd al-Rahman. (2008). Using artificial neural networks models for predicting pancreas behavior. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-546112
Modern Language Association (MLA)
Abid, Bassam Abd al-Rahman. Using artificial neural networks models for predicting pancreas behavior. (Master's theses Theses and Dissertations Master). Philadelphia University. (2008).
https://search.emarefa.net/detail/BIM-546112
American Medical Association (AMA)
Abid, Bassam Abd al-Rahman. (2008). Using artificial neural networks models for predicting pancreas behavior. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-546112
Language
English
Data Type
Arab Theses
Record ID
BIM-546112
