COVID-19 Detection from Chest X-ray Images using CNN - Aşıcı, Elif; Hameed, Alaa Ali; Jamil, Akhtar; Rasheed, Jawad; Rasheed, Jawad (İstanbul Sabahattin Zaim Üniversitesi, 2021)
After Covid-19 was detected in China in December 2019, it spread rapidly and affected the whole world. The similarity of COVID-19 disease with other lung infections makes it difficult to make an accuracy prediction and diagnosis. In addition, with the high spread rate of COVID-19, the need for a fast system and method for diagnosing cases has increased over time. For this reason, studies in the field of health have increased rapidly to prevent this pandemic disease, and various methods base on artificial intelligence (AI) have been developed to support health practitioners in quick decision making. This study focuses on COVID-19 identification with CNN using X-ray images. Moreover, the proposed method was compared with some recent studies for COVID-19 classification. The result presented are in line with the start of the art method as the proposed method provides a good recognition rate for the detection of Covid-19 .
1st International Conference on Computing and Machine Intelligence (ICMI-2021) February 19-20, 2021, Istanbul, Turkey -- Editorial Board Dr. Akhtar JAMIL Dr. Alaa Ali HAMEED -- ISBN: 9786050667578 -- Istanbul Sabahattin Zaim University Yayınları; No. 57.
Keywords: Covid-19; CNN; Deep Learning; Image Processing; Artificial intelligence