Sri Harsha Tavidisetty Rajendra et al., International Journal of Advanced Trends in Computer Science and Engineering, 10(2), March - April 2021, 824 – 830 824 ABSTRACT Corona virus 2019 (COVID-2019), has first appeared in Wuhan, China in December 2019, spread around the world rapidly causing thousands of fatalities. It is caused a devastating result in our daily lives, public health, and also the global economy. It is important to sight the positive cases as early as possible therefore forestall any unfoldment of this epidemic and to quickly treat affected patients. The necessity for auxiliary diagnostic tools has increased as there aren't any accurate automated toolkits available. Recent findings obtained using radiology imaging techniques suggest that such images contain salient information about the COVID-19 virus. Coupling deep learning techniques with radiological imaging may end up within the accurate detection of this disease. This assistance will help to beat the matter of an absence of specialized physicians in the remote villages. Key words: Machine learning, Artificial Intelligence, deep learning. 1. INTRODUCTION An automated model for automatic detection of COVID-19 detection using raw chest X-ray images is presented. The proposal is to come up with a new model to provide accurate diagnostics of COVID-19 using classification methods. The most frequently used testing mechanism currently being employed for COVID-19 diagnosis is a real-time reverse transcription-polymerase chain reaction. Radiological imaging of the chest has crucial roles in the early diagnosis and treatment of this disease [1]. Due to the low RT-PCR sensitivity of around 70%, even if negative results are obtained, symptoms can be traced out by examining the radiological images of patients [2, 3]. It has been found that CT is a sensitive method to detect COVID-19 pneumonia, and can be considered as a screening tool with RT-PCR. CT findings are examined over a long interval after the occurrence of symptoms, and patients generally have a normal CT in the first 2 days. In addition, artificial intelligence-based approaches can be useful in eliminating disadvantages such as the insufficient number of available RT-PCR test kits, test costs, and waiting time of test results. Recently, many radiology images have been used widely for COVD19 detection [2, 3]. . 2. RELATED WORKS In a study on lung CT of patients who survived COVID-19 pneumonia, the most prominent lung disease was seen ten days after the onset of symptoms. At the start of the pandemic, Chinese clinical centers had meagre check kits that are manufacturing a high rate of false-negative results, therefore doctors are inspired to make the diagnosis solely based on clinical and chest CT results. CT is extensively made use for COVID-19 detection in countries where the availability of test kits is scarce. Researchers state that combining clinical image features with laboratory results may help in the early detection of COVID-19. Radiologic images obtained from COVID-19 cases contain useful information for diagnostics. Some studies have come across changes in chest X-ray and CT images before the onset of COVID-19 symptoms. Remarkable discoveries have been realized by investigators in imaging studies of COVID-19. The application of machine learning methods for automatic detection within the medical field has recently gained quality by changing into associate adjunct tools for clinicians. Deep learning, which is a famous research area of Artificial Intelligence, it sanctions the creation of end-to-end models to accomplish the promised results using input data, without the need for the extraction of features manually. Deep learning techniques have been successfully employed in numerous problems such as arrhythmia detection, skin cancer classification, breast cancer detection, brain disease classification, pneumonia detection from chest X-ray images. The COVID-19 epidemic’s rapid rise has opened the need for expertise in this field. This has increased interest and demand in developing automated detection systems using AI techniques. It is an arduous task to provide expert clinicians to every hospital due to the constraint of the number of radiologists. Therefore, such simple and accurate AI models will be so much helpful to overcome this problem and provide timely assistance to patients. Although radiologists play a key role due to their vast experience in this field, the AI technologies in radiology can be used for assistance to obtain an accurate diagnosis. Diagnostic tests performed after 5–13 days are found to be positive in recovered patients. This finding implies that the recovered patients as well may continue to spread the virus. Therefore, Automated Detection of COVID-19 using Deep Learning Sri Harsha Tavidisetty Rajendra 1 , Satish Anamalamudi 2 , Muralikrishna Enduri 3 1 Department of CSE, SRM University-AP, India, Email: rajendra_sriharsha@srmap.edu.in 2 Department of CSE, SRM University-AP, India, Email: satish.a@srmap.edu.in 3 Department of CSE, SRM University-AP, India, Email: muralikrishna.e@srmap.edu.in ISSN 2278-3091 Volume 10, No.2, March - April 2021 International Journal of Advanced Trends in Computer Science and Engineering Available Online at http://www.warse.org/IJATCSE/static/pdf/file/ijatcse511022021.pdf https://doi.org/10.30534/ijatcse/2021/511022021