Hybrid quantum-classical convolutional neural network model for COVID-19 prediction using chest X-ray images

被引:72
|
作者
Houssein, Essam H. [1 ]
Abohashima, Zainab [2 ]
Elhoseny, Mohamed [3 ,4 ]
Mohamed, Waleed M. [1 ]
机构
[1] Minia Univ, Fac Comp & Informat, Al Minya, Egypt
[2] Nanda Univ, Fac Comp Sci, Bani Suwayf, Egypt
[3] Univ Sharjah, Sharjah, U Arab Emirates
[4] Mansoura Univ, Fac Comp & Informat, Mansoura, Egypt
关键词
COVID-19; medical image classification; deep neural networks; quanvolutional neural networks; quantum computing; image processing; GAS SOLUBILITY OPTIMIZATION; DISEASE; 2019; COVID-19; DEEP; ALGORITHM; SUPREMACY;
D O I
10.1093/jcde/qwac003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Despite the great efforts to find an effective way for coronavirus disease 2019 (COVID-19) prediction, the virus nature and mutation represent a critical challenge to diagnose the covered cases. However, developing a model to predict COVID-19 via chest X-ray images with accurate performance is necessary to help in early diagnosis. In this paper, a hybrid quantum-classical convolutional neural network (HQ-CNN) model using random quantum circuits as a base to detect COVID-19 patients with chest X-ray images is presented. A collection of 5445 chest X-ray images, including 1350 COVID-19, 1350 normal, 1345 viral pneumonia, and 1400 bacterial pneumonia images, were used to evaluate the HQ-CNN. The proposed HQ-CNN model has achieved higher performance with an accuracy of 98.6% and a recall of 99% on the first experiment (COVID-19 and normal cases). Besides, it obtained an accuracy of 98.2% and a recall of 99.5% on the second experiment (COVID-19 and viral pneumonia cases). Also, it obtained 98% and 98.8% for accuracy and recall, respectively, on the third dataset (COVID-19 and bacterial pneumonia cases). Lastly, it achieved accuracy and recall of 88.2% and 88.6%, respectively, on the multiclass dataset cases. Moreover, the HQ-CNN model is assessed with the statistical analysis (i.e. Cohen's Kappa and Matthew correlation coefficients). The experimental results revealed that the proposed HQ-CNN model is able to predict the positive COVID-19 cases.
引用
收藏
页码:343 / 363
页数:21
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