Classification of chest diseases from x-ray images using deep learning

In today's modern age, the field of Artificial Intelligence and Health Care are inseparable.Every now and then, doctors and patients use various technology to diagnose diseases.But still, interpreting or identifying diseases through different medical tests such as X-ray or MRI cannot be fully done using artificial intelligence due to the lack of good output from various models.This paper tried to tackle this problem of classifying three diseases that a professional can identify through a chest X-ray image.Prior to this work, many had done similar works but only a few were able to get prediction accuracy over 90%.So, this paper explored that area to get better prediction result and by fitting ResNet50, DenseNet121, MobileNetV2, InceptionNetV3 models, it was seen that ResNet50 outperformed other three models with over 98% accuracy.The result shows that deep learning models can do well classifying diseases from a test image with a very little margin of error.