Clinical Evidence for AI-ECG Technology
Advancing the understanding of heart disease detection through original research and peer-reviewed clinical publications.
View All PublicationsThe Clinical Need
Heart disease is the leading cause of death, yet early detection remains a significant challenge.
80%
of heart disease cases could be prevented with early detection
50%
of patients discover heart disease through an adverse event
1 in 5
heart attacks are silent - the person is not aware of it
Bridging the Diagnostic Gap
Most patients with heart disease are asymptomatic
Physicians have limited front-line technology options to detect heart disease
Most advanced diagnostic tests are expensive and require referral
Payors often discourage advanced diagnostics for asymptomatic patients
Key Publications
Peer-reviewed research demonstrating the clinical value of AI-ECG technology.
Machine Learning Assessment of Left Ventricular Diastolic Function Based on Electrocardiographic Features
JACC | August 2020
Machine Learning of ECG Waveforms to Improve Selection for Testing for Asymptomatic Left Ventricular Dysfunction
JACC | June 2021
A Foundational Vision Transformer Improves Diagnostic Performance for Electrocardiograms
npj Digital Medicine | June 2023
Quantitative Prediction of Right Ventricular Size and Function From the ECG
Journal of the American Heart Association | December 2023
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