A Contemporary Technique for Lung Disease Prediction using Deep Learning

The field of computer science known as machine learning explores algorithms that learn from examples. Classification requires machine learning algorithms that understand how to apply a class label to data from the problem area. An easy-to-understand example is categorizing emails as “spam” or “not spam.” Binary classification predicts one of two classes, whereas multi-class classification predicts one of several classes. In most binary classification tasks, there is one type of normal state and another type of aberrant state. This Project involves how lung disease prediction using x-ray images will predict through the binary classification model implemented, and various python libraries like Tensor Flow, Keras, NumPy, etc. are used. This research project will observe the prediction of lung diseases by using x-ray images and further the output will be predicted with the detailed example and a detailed source code. The implementation will be shown step by step with possible screenshots.