Application the convolutional neural network to determine the probability in chest X-ray images of the presence or absence of the COVID-19 virus
DOI:
https://doi.org/10.5753/reic.2024.2500Keywords:
Artificial Intelligence, Convolutional Neural Network, X-ray image, COVID-19Abstract
Radiographic images, such as chest X-rays, are tools used in disease diagnosis, including types of pneumonia caused by viral infections. Through models based on artificial intelligence, it is possible to develop computational tools that allow the process of image classification from a series of characteristics. Based on this, the present research proposes an algorithm structured as a convolutional neural network to encode and train the classification of chest X-ray images with COVID-19 and regular viruses. The results are obtained using two models. The first model used ResNet50 with an accuracy of 99% for images with COVID-19 and 92% for regular images. The second model used image processing and obtained accuracy of 96% for images with COVID-19 and 92% for regular images.
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