Index Medicus for the Eastern Mediterranean Region (IMEMR) Index Copernicus
ResearchBible J-Gate
I۲OR ROAD
CiteFactor Scientific Indexing Services
SID Magiran
Google Scholar
Department of Biomedical Engineering, Islamic Azad University, E-Campus, Tehran, Iran , javadhosseini1377@yahoo.com
Abstract: (1197 Views)
Background and Aim: 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. Methods: 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. Results: 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. Conclusion: 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.
Jafarnia Dabanloo N, Hosseini S M J, Maghooli K. Detection of COVID-19 Using VGG-16 Neural Network and Classification of Chest X-ray Images. J Mar Med 2024; 6 (1) :64-71 URL: http://jmarmed.ir/article-1-429-en.html