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IJERTV9IS080010
COVID-AI: An Artificial Intelligence System to Diagnose COVID-19 Disease

Somil Vasal , Sourabh Kumar Jain , Ashok Verma

The COVID-19 pandemic is considered the most important global health disaster of the century and the greatest challenge to mankind since World War II. A new class of coronavirus, known as SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is responsible for the occurrence of this disease. COVID-19 disease is similar to pneumonia, so it is difficult to diagnose. Deep learning techniques are gaining increasing importance in the medical diagnosis field by their X- ray scan images. In this research, predictive models are proposed to help the diagnosis of COVID-19 and pneumonia using chest X-ray Images. To make it easy, the graphical user interface will display the severity of the disease on the x-ray image given by the user. Data augmentation has been used to increase the diversity of data without actually collecting new data. We have used different deep learning models such as VGG16, DenseNet121, ResNet50, Inception V3 and Xception models for disease classification and compared the results between those models and found that 98.8% Accuracy is obtained from the DenseNet model.