Models of Learning to Classify X-ray Images for the Detection of Pneumonia using Neural Networks

Abstract

This article describes a comparison of two neural networks, the multilayer perceptron and Neural Network, for the detection and classification of pneumonia. The database used was the Chest-X-Ray data set provided by (Kermany et al., 2018) with a total of 5840 images, with two classes, normal and with pneumonia. to validate the models used, cross-validation of k-fold was used. The classification models were efficient, resulting in an average accuracy of 92.16% with the Multilayer Perceptron and 94.40% with the Convolution Neural Network.