Chest X-ray Classification Based on Deep Neural Network

This study demonstrates how artificial intelligence (AI) is transforming medical diagnosis, particularly for respiratory disorders such as COVID-19 and influenza. The project aims to enhance global healthcare systems by accurately and rapidly identifying respiratory disorders through AI-driven chest X-ray analysis. Given the significant public health implications of infections like COVID-19, the importance of this work is paramount. Convolutional Neural Networks (CNNs) are employed to analyze chest X-ray images and detect patterns indicative of viral infections. Key components of the project include convolutional blocks, the RMSprop optimizer, 2D max pooling, dropout regularization, and the categorical cross-entropy loss function. Two CNN models are developed from scratch to balance complexity and efficacy in X-ray image classification.