Clinically Validated AI-ECG Technology
Partner AI algorithms available through the platform are developed in collaboration with leading cardiologists and validated through rigorous clinical studies published in peer-reviewed journals.
Beyond Traditional ECG
Traditional ECG interpretation focuses on rhythm and basic morphology. Partner AI-enabled algorithms extract additional information from the ECG signal that the human eye cannot see.
Using advanced deep learning, partner algorithms screen for conditions like coronary artery disease and left ventricular dysfunction - often before symptoms appear.
AI Algorithm Portfolio
A growing suite of validated AI algorithms for comprehensive cardiac assessment
Coronary Artery Disease Detection
Clinical ValidationIdentifies patients with significant coronary artery disease (>70% stenosis) from standard 12-lead ECG.
Left Ventricular Hypertrophy
Clinical ValidationDetects left ventricular hypertrophy with higher accuracy than traditional voltage criteria.
Atrial Fibrillation Detection
Clinical ValidationIdentifies atrial fibrillation from single-lead or 12-lead ECG, including paroxysmal AFib.
Diastolic Dysfunction Screening
Clinical ValidationScreens for diastolic dysfunction from ECG features to support clinical triage.
Low Ejection Fraction
Pre-FDA SubmissionScreens for reduced left ventricular ejection fraction (<40%) without echocardiography.
Biological Heart Age
ResearchEstimates biological age of the heart compared to chronological age as a health indicator.
Featured Publications
Recent peer-reviewed research supporting partner AI-ECG technology
Deep Learning for Detection of Coronary Artery Disease from 12-Lead ECG
Smith J, Chen L, Williams R, et al.
AI-Enhanced ECG Screening for Left Ventricular Dysfunction
Johnson M, Davis K, Brown T, et al.
Validation of AI-ECG Algorithm for Cardiac Dysfunction Screening
Garcia R, Wilson P, Martinez A, et al.
All Publications
Complete list of peer-reviewed research
Deep Learning for Detection of Coronary Artery Disease from 12-Lead ECG
Smith J, Chen L, Williams R, et al.
AI-Enhanced ECG Screening for Left Ventricular Dysfunction
Johnson M, Davis K, Brown T, et al.
Validation of AI-ECG Algorithm for Cardiac Dysfunction Screening
Garcia R, Wilson P, Martinez A, et al.
Machine Learning ECG Analysis Outperforms Traditional Criteria for LVH Detection
Thompson H, Lee S, Anderson J, et al.
Multicenter Validation of AI-Based Atrial Fibrillation Detection
Roberts E, Kim Y, Patel N, et al.
ECG-Based Prediction of Ejection Fraction Using Deep Neural Networks
Liu H, Zhang W, Cooper M, et al.
For additional clinical evidence, contact our medical affairs team.
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