Deep Learning Approach to detect Pneumonia

Pneumonia is an inflammatory lung disease which mainly affects the small air sacs known as alveoli. Symptoms of Pneumonia usually involves a mixture of painful or dry cough, chest discomfort, fatigue and difficulties in breathing. So, symptoms of pneumonia can be detected using chest x-rays. Since chest x-rays plays an important role in the detection of pneumonia a deep learning approach can be used for the detection in order to automate it. In this paper the implementation of deep learning approach for the chest x-rays is proposed. This approach has three convolution layers each with 32 neurons with three different channels (3*3). In order to obtain a more robust accuracy, images are transformed based on various parameters. Experimental analysis validates the accuracy of proposed model as 88.68%. The training accuracy and validation accuracy of the model in each epoch is analysed and observed as comparatively high than conventional process.