Determination of COVID-19 pneumonia based on generalized convolutional neural network model from chest X-ray images

作者：

Highlights：

• The chest X-ray images were used to train, validate and test the proposed CNN model.

• The accuracy of the CNN model built on DenseNet-201 has been obtained as 94.96%.

• The bias problem caused by the databases has been prevented.

• The CNN model opens the door to accelerate triage, save critical time, and prioritize resources.

摘要

•The chest X-ray images were used to train, validate and test the proposed CNN model.•The accuracy of the CNN model built on DenseNet-201 has been obtained as 94.96%.•The bias problem caused by the databases has been prevented.•The CNN model opens the door to accelerate triage, save critical time, and prioritize resources.

论文关键词：Corona Virus (COVID-19),Convolutional Neural Network (CNN),Deep learning,Chest X-ray images

论文评审过程：Received 25 March 2021, Revised 28 April 2021, Accepted 28 April 2021, Available online 4 May 2021, Version of Record 8 May 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115141