Research Published in Nature Medicine Demonstrates the Promise of Algorithm-Based Ambulatory Cardiac Monitoring
The collaboration leveraged the iRhythm data science and clinical teams’ expertise in ECG analysis and the company’s proprietary and diversely labeled ECG data set to produce an arrhythmia detection algorithm delivering expert-level classification performance. To date, this is the only model published and shown to reliably detect and label 10 cardiac arrhythmias, as well as distinguish sinus rhythm and noise from artifact, for a total of 12 output classes, potentially giving clinicians a more comprehensive understanding of their patients’ heart rhythms. By applying these sophisticated algorithms to the vast amounts of data captured by continuous ECG monitors, this approach has the potential to increase the accuracy of physician diagnosis and improve the efficiency of expert-human ECG interpretation, so physicans can spend their limited time and resources focused on getting patients the right care.
“As powerful, deep learning algorithms become available for cardiac care, it’s important for the medical community to become more discerning about the overall quality of the algorithms that power the analytical tools we use,” said Dr.
The study results represent the significant effort to evaluate algorithm performance compared to a set of board-certified practicing cardiologists and referenced against a consensus committee of cardiology experts. The publication expands and validates the researchers’ previous findings around the performance of the algorithm, a 34-layer Deep Neural Network, which learned from 91,232 ECG records collected from 53,549 unique patients using the Zio by iRhythm ambulatory continuous cardiac monitoring device. This is the first time a model was developed across this number of arrhythmia classes with a data set of this size.
“Since our company’s inception we have been committed to advancing scientific discovery and methods that improve arrhythmia detection and analysis for better patient care. We are delighted that the Nature Medicine findings expand further our leadership in ECG analysis,” said
You can learn more about the study at www.irhythmtech.com/ai.
iRhythm is a leading digital health care company redefining the way cardiac arrhythmias are clinically diagnosed. The company combines wearable biosensor devices worn for up to 14 days and cloud-based data analytics with powerful proprietary algorithms that distill data from millions of heartbeats into clinically actionable information. The company believes improvements in arrhythmia detection and characterization have the potential to change clinical management of patients.