Paper Info
Title
A Predictive E-Health Information System: Diagnosing Diabetes Mellitus Using Neural Network Based Decision Support System
Abstract
Diabetes Mellitus is a chronic disease and a major cause of several severe complications and death in both developing and developed countries. The number of diabetes cases world-wide has been climbed up drastically over last decades. Hence, it was of utmost important to manage this illness and to develop tools that help clinicians do their job professionally. Artificial neural networks play a major role herein. In this research, a clinical decision support system that helps in diagnosing diabetes has been developed. The system was implemented using a multilayer perceptron artificial neural network. Due to the fact that there is no systematic way to follow in order to determine the number of hidden layers and neurons in MLP, an algorithm was proposed and followed based on the rules-of-thumb previously defined around this issue. As a result, two different topologies were trained and verified using cross validation technique. The topology that exhibited the best averaged accuracy was that of one hidden layer. The data set was obtained from King Abdullah University Hospital in Jordan.
Year
DOI
Venue
2014
10.4018/ijdsst.2014100103
International Journal of Decision Support System Technology
Keywords
Field
DocType
Artificial Neural Network (ANN), Clinical Decision Support System (CDSS), Diabetes Diagnosis, Diabetes Mellitus (DM), E-Health, Information Systems, Multilayer Perceptron (MLP)
Information system,Data mining,Computer science,Decision support system,Network topology,Multilayer perceptron,Artificial intelligence,Clinical decision support system,Health informatics,Artificial neural network,Cross-validation,Machine learning
Journal
Volume
Issue
ISSN
6
4
1941-6296
Citations 
PageRank 
References 
3
0.38
4
Authors
2
Name
Order
Citations
PageRank
Ahmad Al-Khasawneh1849.65
Haneen Hijazi230.38