Lung disease classification on X-ray Images using Machine Learning 

The mission of this project is to develop an intelligent system for the multiclass classification of lung diseases using Convolutional Neural Networks (CNNs) applied to chest X-ray images. The study aims to investigate how image enhancement techniques influence model performance by improving image quality and feature visibility.

By comparing results before and after enhancement, the project seeks to demonstrate the effectiveness of preprocessing in increasing classification accuracy, precision, recall, and F1-score. Ultimately, this work contributes toward more reliable and efficient computer-aided diagnosis systems in medical imaging.