ABSTRACT
In this paper, we study the Convolutional Neural Network (CNN) applications in medical image processing during the battle against Coronavirus Disease 2019 (COVID-19). Specifically, three CNN implementations are examined: CNN-LSTM, COVID-Net, and DeTraC. These three methods have been shown to offer promising implications for the future of CNN technology in the medical field. This survey explores how these technologies have improved upon their predecessors. Qualitative and quantitative analyses have strongly suggested that these methods perform significantly better than the commensurate technologies. After analyzing these CNN implementations, it is reasonable to conclude that this technology has a place in the future of the medical field, which can be used by professionals to gain insight into new diseases and to help in diagnosing infections using medical imaging. © 2021, EasyChair. All rights reserved.