MATLAB for the 2025 George B. Moody PhysioNet Challenge
Overview
In this webinar, we will explore how MATLAB can be used to train a neural network that predicts if a patient has Chagas disease based on electrocardiogram (ECG) data. In support of the 2025 George B. Moody PhysioNet Challenge but open to everyone, this workshop is designed to give participants ideas and inspiration to improve their projects. We’ll start with a brief introduction to MATLAB, go through some options for importing, visualizing, and preprocessing signal data, then dive into training, testing, and using a neural network.
Highlights
- Work with large datasets without running out of memory
- Preprocess signals to achieve consistency when working with messy data
- Extract features for deep learning
- Train a neural network to classify signal data
About the Presenter
Grace Woolson is a Student Programs Engineer at MathWorks. Specializing in data science, she provides technical resources for students participating in competitions and for those just looking to learn more about working with data and AI.
