Paper Title
Automated Pneumonia Detection from Chest X-Ray using Deep Learning

Abstract
Pneumonia remains a significant global health concern, contributing to high morbidity and mortality rates. Rapid and accurate diagnosis of pneumonia is crucial for timely intervention and effective patient care. In recent years, deep learning techniques have shown immense potential in the automated detection of diseases from medicalimages. This research paper presents an innovative approach to pneumonia detection. The studyleverages a convolutional neural network (CNN) architecture designed specifically for medical image analysis, trained on a large and diverse dataset of chest X-ray images. Furthermore, this research explores the model's interpretability and the impact of various hyperparameters on its performance. Additionally,the study emphasizes the importance of ongoing research and development in the field of medical imaging and artificial intelligence to further refineand expand the capabilities of these systems.