Optimizing Pneumonia and Tuberculosis Detection using GAN and CNN

Pneumonia and tuberculosis (TB) are serious respiratory diseases that continue to pose significant global health challenges, leading to high rates of illness and death, particularly in low- and middle-income countries. Our project focuses on developing a prediction model specifically designed to detect pneumonia, tuberculosis, or both. Using deep learning algorithms like GANs and CNN, this model enhances healthcare by enabling quicker diagnosis and proactive intervention. It offers a cost-effective solution for remotely screening patients, helping to improve access to timely care and reduce the burden on healthcare systems.