Multiclass Medical X-ray Image Classification using Deep Learning with Explainable AI

Abstract

Abstract: COVID-19, also known as novel coronavirus, created a colossal health crisis worldwide. This virus is a disease that basically comes from Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). A novel coronavirus, COVID-19, is the infection caused by SARS-CoV-2. The early detection of COVID-19 and the accurate separation of non-COVID-19 cases at the lowest cost and in the early stages of the disease are among the main challenges in the current COVID-19 pandemic. As pneumonia also is a significant indication of COVID-19, then it is necessary to detect it in the early stages. Another challenge is that it is very elusive to classify the chest xray between COVID-19 and pneumonia as the visual indications for both the labels are quite similar. The application of deep learning in the field of radiologic image processing reduces false-positive and negative errors in the detection of this disease and could offer a unique opportunity to provide fast, cheap, and safe diagnostic services to patients. Also, the Deep learning models are considered to be the “black boxes”. According to the ethics of AI in radiology, “transparency, interpretability, and explainability are necessary to build patient and provider trust”