vinicius-trev/xrayaid

This repository exposes the final year computer engineering undergraduate project called xRayAID

xRayAID

Overview

This repository exposes the final year computer engineering undergraduate project called xRayAID

The xRayAID is a classification tool capable of receiving frontal thorax radiography to speed up the diagnosis of pneumonia using machine learning. That was done by using a slightly modified DenseNet-121 network architecture trained on the Radiological Society of North America (RSNA) public dataset. The results showed that this tool is able to help doctors to identify pneumonia scenarios, achieving a validation accuracy of 87.9%.

Hardware and Plataform Used

• Intel Core i7-3930k, 6 Cores 12 Threads
• 32 GB 1600MhZ RAM
• 1 x NVIDIA GeForce RTX 2070

Platform and Software

• Ubuntu 18.04 LTS
• Python 3.5.4 (training)
• Python 3.8 (inference/API)

Instalation and More Info

Each of the subfolders on this repository contains a README file explaining all the steps.

Results

Validation Loss

Validtion Accuracy

Validation ROC AUC

Contact

If you have any quesions, please post it on github issues or email at [email protected]

Also, if you use any of this work, please, cite me.