Classification of Pneumonia via a Hybrid ZFNet-Quantum Neural Network Using a Chest X-ray Dataset.

Journal: Current medical imaging
Published Date: Jan 1, 2024

Abstract

INTRODUCTION: Deep neural networks (DNNs) have made significant contributions to diagnosing pneumonia from chest X-ray imaging. However, certain aspects of diagnosis and planning can be further enhanced through the implementation of a quantum deep neural network (QDNN). Therefore, we introduced a technique that integrates neural networks with quantum algorithms named the ZFNet-quantum neural network for detecting pneumonia using 5863 X-ray scans with binary cases.

Authors

  • Tayyaba Shahwar
    Department of Electrical Engineering, Superior University, Lahore 54000, Pakistan.
  • Fatma Mallek
    Faculty of Engineering, Uni de Moncton, NB, E1A3E9, Canada.
  • Ateeq Ur Rehman
    Department of Computer Science, Abdul Wali Khan University Mardan, Pakistan.
  • Muhammad Tariq Sadiq
    School of Automation, Northwestern Polytechnical University, Xi'an 710129, China.
  • Habib Hamam
    School of Electrical Engineering, Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, South Africa.

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