A Survey on Deep Learning Advances and Emerging Issues in Pneumonia and COVID19 Prediction

Abstract

As the COVID19 pandemic evolves and coronavirus mutates to different variants, a high workload falls on the shoulders of doctors and radiologists. Identifying COVID19 through X-ray and Computed Tomography (CT) scanning in a short amount of time is vital because it helps doctors start the COVID19 treatment in the early stages. Deep Learning algorithms showed tremendous results in automating COVID19 detection using X-ray and CT scans. As there are not many survey papers on COVID19 detection using deep learning techniques, the goal of this paper is (1) to give a thorough discussion of COVID19 prediction considering Computer Vision problems like COVID19/pneumonia classification, detection, and segmentation, (2) to address new advances in deep learning like Transformers, GANs, and LSTMs, and (3) to cover technical issues like data security and data scarcity of X-ray and CT scans in COVID19.