Quality data, robust analysis
99% mean analysable time
The Zio Service provides uninterrupted data and high diagnostic yield to diagnose arrhythmias accurately first time. Turakhia, M., et al. Diagnostic Utility of a Novel Leadless Arrhythmia Monitoring Device. The American Journal of Cardiology, 2013
deep learning
Our collaboration with the Stanford Machine Learning Group shows that the Zio service can provide the reliability of an expert cardiologist. This could only only be achieved because of the large amounts of diverse data generated by the Zio Service.
Certified Cardiac Technician Review
We employ certified cardiac technicians
specialised in advanced arrhythmia interpretation. Our experts review all reports prior to posting, giving confidence and assurance with the Zio Service.
In collaboration with the Stanford Machine Learning Group, over 91,000 Zio records were processed through a deep neural network (DNN) to see if the algorithm could learn to identify various arrhythmia classes.
The quality and quantity of Zio data enabled the DNN to accurately detect and identify 10 arrhythmia classes while separating sinus rhythm and artifact for a total of 12 output classes. These results were compared to those of board-certified experts, confirming equivalent performance.
To learn more about the collaboration, visit the Stanford Machine Learning Group online