Pneumonia Detection using Deep Convolutional Neural Networks by using digital chest X-ray

Abstract

Pneumonia is a widespread and severe respiratory disease that arises from inflammation of the lung tissue, resulting in impaired functioning. It is a leading cause of death worldwide. Prompt recognition and treatment of pneumonia are essential to mitigating disease severity and duration, improving patient outcomes, and ensuring timely and appropriate medical intervention. Instead of self-interpreting chest X-rays, which can be prone to errors, technology and artificial intelligence (AI) can help accurately diagnose pneumonia and analyze X-ray images. This project aims to develop a system that uses AI to detect pneumonia by making use of chest X-ray images as the primary data source (data is open source). The proposed system incorporates machine learning algorithms to analyze a variety of chest X-ray datasets, and the accuracy and reliability of the system in identifying pneumonia in terms of diagnostic accuracy are evaluated and compared with several similar models. The ultimate goal of this project is to create a reliable tool that healthcare professionals can use to accurately and efficiently diagnose pneumonia, thus ensuring timely treatment for patients.