Deep Learning Driven X-ray Classification for Pneumonia Detection Using CNN

Major deaths (55% or 1.5 million) of LRI (Lower Respiratory Infections) are caused due to Pneumococcal pneumonia. LRI is the 5th highest cause of demise as mentioned by the Global Burden of Disease Study 2015. Health organization suffers from a lack of Physicians. A Physician handles so many cases which leads to misdiagnoses. To resolve all these issues we came up with an easy-to-handle, and implemented in health organizations, the CNN model. The main aim of this model is to help the healthcare professionals by providing them with a tool which will help them detect Pneumococcal pneumonia. With the help of this tool, the work strain of a doctor can be reduced. This model is developed without any pre-trained model and for better accuracy, an immense dataset is used. All the X-ray images were pre processed before being introduced to the neural network. Different layers have been used to make the model more precise and make it adaptable for X-ray images under different conditions. The aim is to combine deep learning concepts with healthcare to make a positive and meaningful impact in the healthcare industry.