Pneumonia disease is caused by viruses and bacteria which affect one or both lungs. It is the most dangerous disease that causes huge cancer death worldwide. Early detection of Pneumonia is the only way to improve a patient's chance for survival. We can detect this disease from X-ray or Computed Tomography (CT) lung images using Deep Learning Techniques. This research paper provides a solution to medical practitioners in predicting the impact of virus as high-risk, low-risk and medium-risk among the population being tested through various Deep Learning techniques such as Convolutional Neural Networks (CNN), Arti cial Neural Network (ANN) and Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) cells. We observed 3000 CT images of Pneumonia con rmed patients and achieved the accuracy resulting 98-99%. The performance of the classi ers are evaluated using parameters such as confusion matrix, accuracy, F-measure, precision and Recall. The results proves that deep learning afford a tting tool for fast screening of Pneumonia and discovering high-risk patients and preventing them by providing suitable medical remedies.

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