Deep Learning-Based COVID-19 Detection Using CT and X-Ray Images: Current Analytics and Comparisons

作     者：Rehman, Amjad Saba, Tanzila Tariq, Usman Ayesha, Noor 

作者机构：CCIS Prince Sultan Univ Artificial Intelligence & Data Analyt Lab Riyadh Saudi Arabia Prince Sattam bin Abdulaziz Univ Coll Comp Engn & Sci Al Kharj Saudi Arabia Zhengzhou Univ Sch Clin Med Zhengzhou Peoples R China 

出 版 物：《IT PROFESSIONAL》 (IT Prof)

年 卷 期：2021年第23卷第3期

页      面：63-67页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Prince Sultan University Saudi Arabia [COVID19-CCIS-2020{54}] 

主　　题：COVID-19 Deep learning Pathogens Pandemics Computed tomography Data science Market research 

摘      要：Currently, the world faces a novel coronavirus disease 2019 (COVID-19) challenge and infected cases are increasing exponentially. COVID-19 is a disease that has been reported by the WHO in March 2020, caused by a virus called the SARS-CoV-2. As of 10 March 2021, more than 150 million people were infected and 3v million died. Researchers strive to find out about the virus and recommend effective actions. An unprecedented increase in pathogens is happening and a major attempt is being made to tackle the epidemic. This article presents deep learning-based COVID-19 detection using CT and X-ray images and data analytics on its spread worldwide. This article s research structure builds on a recent analysis of the COVID-19 data and prospective research to systematize current resources, help the researchers, practitioners by using in-depth learning methodologies to build solutions for the COVID-19 pandemic.