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EchoSolv™ AS

Identify high-probability severe aortic stenosis (sAS) patients accurately, quickly, simply

Provides a clear picture of your patient’s heart by analyzing measurements, not images

What is EchoSolv AS?

  • Measurement-based AI clinical decision support for severe aortic stenosis probability1

  • Standardized severe AS probability and guideline check from routine echo measurements1

  • Designed to fit existing workflows (no EMR integration required)1

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patient-and-cardiologist

Using the same echo measurements already collected,1
EchoSolv AS delivers:

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Consistent assessment

Consistent severe AS probability and guideline check from measurements1

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Second reader support

Helps prioritize which studies need closer review1,2

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Real-world readiness

The AI does not use LVOT measurements1

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Faster clinical review

Uses standardized, measurement-based AI and guideline analysis to help you review studies faster1,2

EchoSolv AS finds hidden cases

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45.7% misclassified by clinicians; women were disproportionately affected (54.4% women vs 38.6% men)3 

EchoSolv AS supports faster clinical review

By applying standardized, measurement-based (AI and guideline) analysis, EchoSolv AS helps clinicians review studies more efficiently while ensuring cases with a high-risk probability are not overlooked.1,2

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24.1% Reduction

Review Time1
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82.2% Sensitivity

Detection Rate2
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99.2% NPV

Rules Out Severe AS2
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Learn more about our FDA-cleared, clinically validated innovation

In this video, "risk" refers to the probability of severe aortic stenosis derived from the multi-dimensional relationship of echocardiographic measurements, as described in the Instructions for Use. This information is intended to support, not replace, physician judgment, guideline interpretation, or patient review.

References
  1. Echo IQ Ltd. (2024). Clinician user manual – EchoSolv AS (Version 1.5.2) (IFU-003). Sydney, NSW.
  2. Strom JB, Playford D, Stewart S, Strange G. An Artificial Intelligence Algorithm for Detection of Severe Aortic Stenosis: A Clinical Cohort Study. JACC Adv. 2024 Sep 25;3(9):101176. doi: 10.1016/j.jacadv.2024.101176.
  3. Strange G, Stewart S, Watts A, Playford D. Enhanced detection of severe aortic stenosis via artificial intelligence: a clinical cohort study. Open Heart. 2023 Jul;10(2):e002265. doi: 10.1136/openhrt-2023-002265.