COVID-19 Diagnosis Using Transfer Learning Techniques and Applications on Chest X-Ray Images

Abstract

COVID-19 is a viral disease caused by a new type of coronavirus called SARS-CoV-2. The World Health Organization (WHO) declared it a pandemic due to this disease spreading over many countries. Currently, there is no medicine available to prevent or cure infectious diseases. COVID-19 samples are commonly tested using reverse transcription polymerase chain reactions (RT-PCR), which are more expensive and take 24 hours to deliver either a positive or negative result. This chapter aims to develop a rapid and accurate medical diagnosis support system for COVID-19 in chest x-ray images by combining transfer learning techniques with the KNN algorithm. There are multiple approaches to building a classification system for analyzing radiographic images in deep learning. In this way, the knowledge acquired from a pre-trained convolutional neural network can be used to solve a new problem. Stacking is a machine learning method that combines the performances of the many transfer learning-based models to ensure the robustness of the proposed system.