CASE STUDY: Identifying the most at-risk structural heart patients

Identifying the Most At-Risk Structural Heart Patients

CardioCare’s artificial intelligence algorithms predict trends to help physicians:

  • Identify undiagnosed severe aortic stenosis 
  • Track progression of moderate aortic stenosis
Trained on the largest commercial database of more than 500,000 deidentified echocardiograms to improve the quality of patient care. 

How do you know if a severe patient has been missed? 

Related Articles


egnite, Inc. Announces Groundbreaking Research from its Database at American College of Cardiology Conference 2023

Two Bodies of Research Led by Philippe Généreux, MD and Colleagues were Presented Today at 2023 ACC Annual Meeting. Key Findings Demonstrate Increased Mortality Across All Degrees of Severity of Aortic Stenosis, Suggesting the Need to Re-Evaluate Currently Recommended Timing of Intervention, and Highlight the Importance of the Extent of Cardiac Damage as the Main Driver for Outcomes

Exciting news! CardioCare has expanded into heart failure. Learn more to see how these new insights can help improve outcomes for your patients.