aspg-3-543-1791417349 20261007235549 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2020 2 1 Shaymaa Adnan Abdulrahma Department of Computer Engineering, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq and a PhD Student at Ain Shams University, Egypt Abdel-Badeeh M. Salem Department of Computer &Information Science, Ain Shams University, Cairo, Egypt COVID-19 infection is one of the most dangerous respiratory viruses, and the early detection of this disease reduces the speed of its spread among people. The goal of this virus is to infect the lung by creating patchy white shadows inside the lungs. This paper presents an intelligent method based on the deep learning technique to analyze the medical images of respiratory diseases. Two data set was used in this experiment first dataset is normal lungs taken from the Kaggle data repository. In contrast, abnormal lungs were taken from (https://github.com/muhammedtalo/COVID-19). The results show that the proposed system identifies the COVID-19 cases with an accuracy of 90%. 2020 05 13 543 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.020102 https://www.americaspg.com/journal/3/article/543 https://www.americaspg.com/storage/01723762054.pdf