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.
Voir la description complète du projetEric Croiset;Lena Ahmadi
University of Ottawa Heart Institute Foundation
Life Sciences
Health and Related Sciences & Technology
University of Waterloo
Accelerate