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Sensors and Materials
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Sensors and Materials, Volume 32, Number 7(2) (2020)
Copyright(C) MYU K.K.
pp. 2375-2385
S&M2266 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2813
Published: July 20, 2020

Using Artificial Neural Network to Predict a Variety of Pathogenic Microorganisms [PDF]

Yu-Hsuan Liao, Yu-Ning Yu, Maysam F. Abbod, Chung-Hung Shih, and Jiann-Shing Shieh

(Received December 15, 2019; Accepted April 20, 2020)

Keywords: electronic nose, pneumonia, artificial neural network

In this study, an electronic nose is used to record breathing data from healthy and pneumonia patients. The electronic nose records resistance data using a microarray of 11 sensors made of a metal oxide semiconductor. The recorded data are fed to an artificial neural network (ANN), which is used to train a model for the detection of infections. Initially, five patients’ data are used to construct the ANN model. Then, another two patients’ data are used to test the accuracy of the model. In this preliminary study, the ANN achieved good results, showing that it can be further developed into an efficient online pneumonia detection system in the near future.

Corresponding author: Chung-Hung Shih, Jiann-Shing Shieh


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Cite this article
Yu-Hsuan Liao, Yu-Ning Yu, Maysam F. Abbod, Chung-Hung Shih, and Jiann-Shing Shieh, Using Artificial Neural Network to Predict a Variety of Pathogenic Microorganisms, Sens. Mater., Vol. 32, No. 7, 2020, p. 2375-2385.



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