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Proceedings of the 11th International Conference on Robotics, Vision, Signal Processing and Power Applications pp 467–473Cite as

Development of COVID-19 Prediction Models from Chest X-Ray Using Transfer Learning

Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 829)

Abstract

Due to the outbreak of corona virus disease (COVID-19) globally, many countries are facing shortages of testing kits and medical resources. Moreover, the current COVID-19 swab test cannot easily perform due to asymptomatic patients. To assist the medical staff, few studies have proposed to detect and classify COVID-19 cases by analyzing radiological images. In this paper, we aim to develop an alternative method using chest X-ray images to provide an automatic and faster diagnosis. Convolutional neural network models that can detect the presence of COVID-19 and pneumonia infection from chest X-ray images are developed by exploiting transfer learning techniques. Three models were developed for comparison, the models yielded an accuracy of 97.3%, 98.2%, and 97.3% respectively.

Keywords

  • COVID-19
  • X-ray
  • Convolutional neural network

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Authors and Affiliations

  1. University of Nottingham Malaysia, 43500, Semenyih, Selangor, Malaysia

    Shaline Koh Jia Thean, Marwan Nafea & Hermawan Nugroho

Authors
  1. Shaline Koh Jia Thean
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  2. Marwan Nafea
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  3. Hermawan Nugroho
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Corresponding author

Correspondence to Hermawan Nugroho .

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Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia

    Assoc. Prof. Nor Muzlifah Mahyuddin

  2. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia

    Dr. Nor Rizuan Mat Noor

  3. School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia

    Assoc. Prof. Harsa Amylia Mat Sakim

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Thean, S.K.J., Nafea, M., Nugroho, H. (2022). Development of COVID-19 Prediction Models from Chest X-Ray Using Transfer Learning. In: Mahyuddin, N.M., Mat Noor, N.R., Mat Sakim, H.A. (eds) Proceedings of the 11th International Conference on Robotics, Vision, Signal Processing and Power Applications. Lecture Notes in Electrical Engineering, vol 829. Springer, Singapore. https://doi.org/10.1007/978-981-16-8129-5_72

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