Using artificial neural network to predict a variety of pathogenic microorganisms

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

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)2375-2385
Number of pages11
JournalSensors and Materials
Issue number7
Publication statusPublished - Jul 20 2020


  • Artificial neural network
  • Electronic nose
  • Pneumonia

ASJC Scopus subject areas

  • General Materials Science
  • Instrumentation


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