MIT EECS | Fairbairn Undergraduate Research and Innovation Scholar
Prediction of Cardiac Health from Electrocardiograms (ECGs) using Machine Learning
- Artificial Intelligence and Machine Learning
Collin M. Stultz
Electrocardiograms (ECGs) use electrodes to detect the electrical changes that occur during each heartbeat. Changes in the normal ECG pattern can be indicative of cardiac disease or dysfunction. The immediate goal of this project is to evaluate existing methods as well as develop new methods to measure morphologic variability, the beat-to-beat changes in ECG signal, in a new patient cohort.
I am majoring in Computer Science with a focus on applications in biology. In the past I have had the opportunity to do research in a wet-lab. Through the SuperUROP, I hope to develop my technical, research, and communication skill-set. I am excited to commit to a year-long research project, and apply the material from classes in machine learning towards my interest in medicine.