Artificial Intelligence and Machine Learning in the Interpretation of Wide-Complex Tachyarrhythmia

Wide-Complex Tachyarrhythmia (WCT) is an abnormality in which the heart rate is elevated and QRS complex duration is increased. An electrocardiogram (ECG) is a simple and quick test used to review heart functioning, so ECG images can be used to determine whether a patient is having an abnormal heart rhythm such as WCT. A WCT diagnosis based on the ECG can be difficult as it can take a lot of time and considerable expertise to make an accurate interpretation. Our study aims to use deep machine learning to develop a model or artificial intelligence (AI) system, trained on data from a patient population diagnosed with WCT. A successful AI system can quickly analyze and interpret ECG images with to help guide a quick and accurate WCT diagnosis. At the University of Ottawa Heart Institute, an accurate AI system can be beneficial for ECG interpretations, specifically with regards to WCT diagnosis.

Faculty Supervisor:

Eric Croiset;Lena Ahmadi


Nishita Saha


University of Ottawa


Engineering - chemical / biological




University of Waterloo



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