Pneumonia Detection Using Convolutional Neural Networks


The aim of this work is to develop an efficient neural network to perform binary classification on X-ray images.

This work implement the architecture proposed in the paper "An Efficient Deep Learning Approach to Pneumonia Classification in Healthcare, Journal of Healthcare Engineering, 2019, Okeke Stephen et al".


The dataset is organized into 3 folders (train, test, val) and contains subfolders for each image category (Pneumonia/Normal). There are 5,863 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal).

You can found it on kaggle at

Convolutional Neural Network

In Okeke Stephen et al., authors proposed the following architecture: After reimplementing this model with the Keras Sequential API, we obtain the following architecture:


After model testing, we obtain the following results: Which leads to an accuracy of 0.89.