Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/21115
Title: Using Artificial Neural Network to Predict a Variety of Pathogenic Microorganisms
Authors: Liao, Y-H
Yu, Y-N
Abbod, M
Shih, C-H
Shieh, J-S
Keywords: Pneumonia;Artificial neural network;Electric nose
Issue Date: 2020
Publisher: MDPI
Citation: Sensors
Abstract: In this study, an electronic nose is used to record breathing data from healthy patients and pneumonia patients. The electronic nose records resistance data using a micro-array of 11 sensors. The recorded data is fed to Artificial Neural Network (ANN) which is used to train a model for detection of infections. The ANN has performed accurate classification which can be further developed to an online efficient pneumonia detection system. Initially, five patients’ data are used to build up the ANN model. Then, another two patients’ data are used to test the accuracy of the model. The results show that the model predicts the same outcome that is diagnosed by Taipei Medical University Hospital where samples have to be cultured to identify whether patients have pneumonia or not. In this preliminary study, ANN has achieved good results which can be further developed to an online efficient pneumonia detection system in the near future.
URI: http://bura.brunel.ac.uk/handle/2438/21115
ISSN: 1424-8220
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdf1.15 MBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.