Using Convolutional Neural Networks to Identify Diseases in X-ray Chest Images (A Case Study)
Program: Data Science Master's Degree
Location: Not Specified (remote)
Student: Michael Pilecky
My project is a case study using convolutional neural networks (CNNs) to identify diseases shown in chest X-ray images. CNNs are essentially neural networks designed to analyze and classify images. The studied diseases are tuberculosis (TB), COVID-19, and pneumonia. My objective for this project was to create a CNN model to identify the studied diseases from chest X-ray images as accurately and quickly as possible. I also wanted the CNN model to classify the X-ray images solely based on disease characters.