Identifying Heart Anomalies from Electrocardiograms
Pre-process recorded ECGs and engineer features to detect heart conditions early
Heart complications are still the leading cause of death in the US
Such conditions are often asymptomatic, and human analysis of electrocardiograms (ECG) is required to identify the disease. Unfortunately, if the condition is not promptly recognized and treated, the consequences can be fatal.
We identify anomalies in a fast and reliable way
Our models achieve state of the art performance (F1-Score between 0.93 and 0.99) and are the first known to perform consistently across countries, hospitals and recording standards.
Leverage machine learning to help doctors
Our work has been peer-reviewed and published in IEEE Journal of Biomedical and Health Informatics, one of the top journals in the field.
Why is the Interpretable AI solution unique?
Fast and reliable detection
Our algorithm requires less than 30 milliseconds to run its full pipeline, making it viable in a real-time setting
Consistency across recording standards
This is the first known method to achieve high performance across countries, hospitals and recording standards