Pneumonia Diagnosis from Chest X-Ray Images Using a Neural Network, Evaluating Precision, Accuracy and Recall

Abstract

This study features a novel solution to diagnose pneumonia using machine learning. Pneumonia is a deadly disease that accounts for 16% of all deaths of children under five years worldwide. Pneumonia is an infection that causes the alveoli sacs inside the lungs to swell with liquid pus. This disease is deadly, making the early diagnosis a priority. Chest-X rays are one way of diagnosing pneumonia; however, they require the presence of a trained specialist, hence this project, aiming to create a quicker and more accessible procedure that integrates an 89% accurate model with a precision of 96% and a recall of 92%. This model, considering its accuracy, precision and recall present a solution that takes milliseconds to identify pneumonia as opposed to an actual specialist taking minutes. The model is also accessible to all with a computer and scanning equipment, increasing accessibility.