Abstract

SARS (Severe Acute Respiratory Syndrome) or COVID 19, When a sick person talks, sneezes, or coughs, microscopic droplets of mucus or saliva are discharged from their respiratory system, carrying the corona virus-2. It spreads quickly by direct contact with an infected person, touching, or holding contaminated things or surfaces. Pneumonia is a different viral illness that is often caused by an infection brought on by a bacterium in the lung alveoli. Pus accumulates in lungs' tissue that has been infected and is inflamed. Experts perform physical examines and evaluate the patient using chest X-rays, ultrasounds, or lung biopsies to ascertain whether the patient has these conditions. The patient will die as a result of a misdiagnosis, inadequate treatment, and illness neglect. Deep learning advancements assist medical professionals in diagnosing individuals with various disorders by supporting their procedure for making decisions. Using chest X-ray image, researcher uses a versatile or effective deep learning method which applies the CNN model to anticipate and identify patients who are both non-impacted and impacted from the condition. An accuracy rate was achieved by the trained model during the performance training. According to test results, the researcher’s study identify and forecast COVID 19 and Non-COVID.