Clinical Evidence

Our AI algorithms are backed by rigorous clinical research and real-world validation studies.

15M+

ECGs analyzed in development

50+

Peer-reviewed publications

20+

Conditions detected

FDA

Cleared algorithms

Key Publications

Artificial Intelligence-Enabled ECG for Detection of Cardiac Dysfunction

Chen, S., Rodriguez, J., et al. · Nature Medicine · 2024

Demonstrated 94% accuracy in detecting left ventricular dysfunction
View Paper

Validation of AI-ECG in Real-World Clinical Settings

Torres, M., Walsh, J., et al. · JAMA Cardiology · 2023

Prospective study of 50,000+ patients showed significant improvement in early detection
View Paper

Cost-Effectiveness of AI-Assisted ECG Interpretation

Kim, R., Foster, A., et al. · Health Affairs · 2023

Economic analysis showing positive ROI within 6 months for most health systems
View Paper

AI-ECG for Screening of Hypertrophic Cardiomyopathy

Chen, S., Patel, N., et al. · Circulation · 2024

Novel algorithm achieving 91% sensitivity for HCM detection
View Paper

Rigorous Validation Process

Every AI-ECG algorithm undergoes extensive validation before clinical deployment. Our process ensures safety, accuracy, and reliability.

1

Development Dataset

Training on millions of annotated ECGs with confirmed diagnoses

2

Internal Validation

Testing on held-out datasets with blinded evaluation

3

External Validation

Prospective studies at independent clinical sites

4

Regulatory Clearance

FDA 510(k) clearance for clinical use

Continuous Monitoring

Ongoing performance tracking and algorithm updates

Validation process diagram

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