Pneumonia Identification Using Deep Learning Models

In the era of artificial intelligence, the key goal is to build a model which could think like a human and could give a quick response. It is better to rely on these models as it is more accurate and could identify the problem more accurately which couldn't be identified by the human eye. In this paper, deeplearning models are trained to identify pneumonia. The key goal of the research paper is to assist the chest doctor in making decisions quickly, accurately, and conveniently, it is important to develop a reliable method for detecting pneumonia using X-rays. The model is implemented in a way that it includes both a data set of picture data and the diagnosis of pneumonia by using deep learning methods based on neural networks. The test and assessment will be used on a variety of chest X-ray pictures. According to the findings of our proposed work, it was found ResNet-152V2 gave a maximum accuracy of 97.7 % among all the other models that we used while comparing all the models.