Scholarlink

Covid-19 is a highly infectious disease caused by the SARS-CoV-2 virus. The virus primarily spreads through respiratory droplets and close contact that affects the upper respiratory tract as well as the lungs. Chest X-ray images can be used to detect and analyze Covid-19 patients. This research investigates the hybrid quantum computing with convolutional neural network, enables the execution of computations for the analysis of Covid-19 images when circuits with a large number of qubits are currently impractical. The proposed hybrid QCNN architectures consist of two phases: in phase 1 using quantum circuit to resizes chest X-ray images and in phase 2, the detection of Covid-19 is performed, in which CNN model is used. The proposed hybrid QCNN model achieved accuracy of 60% on the Covid-19 chest X-ray images dataset. This study demonstrates how quantum neural networks may be used to identify Covid-19 patients. These results suggest that the suggested hybrid QCNN model may increase the diagnostic accuracy of Covid-19.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Hybrid Quantum Convolutional Neural Network Model for Detecting Covid-19 from Chest Radiographs Images

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Madhulata Kumari,
  • Kanad Ray,
  • Saurav Mallik,
  • Aimin Li

摘要

Covid-19 is a highly infectious disease caused by the SARS-CoV-2 virus. The virus primarily spreads through respiratory droplets and close contact that affects the upper respiratory tract as well as the lungs. Chest X-ray images can be used to detect and analyze Covid-19 patients. This research investigates the hybrid quantum computing with convolutional neural network, enables the execution of computations for the analysis of Covid-19 images when circuits with a large number of qubits are currently impractical. The proposed hybrid QCNN architectures consist of two phases: in phase 1 using quantum circuit to resizes chest X-ray images and in phase 2, the detection of Covid-19 is performed, in which CNN model is used. The proposed hybrid QCNN model achieved accuracy of 60% on the Covid-19 chest X-ray images dataset. This study demonstrates how quantum neural networks may be used to identify Covid-19 patients. These results suggest that the suggested hybrid QCNN model may increase the diagnostic accuracy of Covid-19.