Pneumonia Identification and Classification Using CNN Model Based on Chest X-Ray Image in Healthcare

Pneumonia is a bacterial, viral, or fungal disease within one or even both lungs. It is a serious disease where the air sacs in both lungs fill up with pus as well as other substances. Many architectures and models were developed to evaluate such diseases, but still, the possibility to further enhancement. We built a CNN model to identify and categorise Pneumonia disease in the lungs using CXR images. The dataset was developed and pre-processed by the Kaggle CXR dataset. In the research, the convolutional neural network method has been used in conjunction with other data augmentation approaches to improve classification accuracy which will help to enhance the training and validation accuracies, as well as characterisation of the precision of the CNN model and achieve various results. Our model's training accuracy and validation accuracy are 0.9784 and 0.9511, respectively, and its training loss and validation loss are 0.0634 and 0.1476.