Detection of COVID-19 Using VGG-16 Neural Network and Classification of Chest X-ray Images

With the increase in the number of infections and deaths of covid-19, the need is felt to use artificial intelligence and machine learning tools to diagnose the corona virus quickly and on time. In this study, using chest x-ray images and VGG-16 deep neural network, an automatic system was designed and implemented to detect cases of covid-19.

In this research, chest x-ray images obtained from the Kaggle database were used. The design of this study included: data sampling, training division, creating directories, transferring images to their own folders, classifying images, creating the proposed VGG-16 model in Python programming language and Keras and Tensorflow libraries, evaluation of the proposed model and finally the creation of the confusion matrix and their analysis and interpretation.

The accuracy and Precision of the proposed model for the positive Covid-19 class were 91 and 93%, respectively. Also, the recall rate and F1-Score for cases with covid-19 were 94% and 88% respectively.

Due to the high accuracy and precision of the proposed model, it can be used to diagnose covid-19 and separate COVID-19 cases from healthy cases and also be used as an auxiliary tool to help doctors diagnose this disease.