During the follow-up period of up to 5 years, 444 patients died, highlighting the poor outcomes associated with HFpEF.1 The AI model was able to identify patients with worse survival, demonstrating its capacity to meaningfully improve patient outcomes.
Ross Upton, PhD, CEO and Founder of Ultromics, said: "Our research demonstrates the tremendous potential of AI in revolutionizing the detection of HFpEF. EchoGo® Heart Failure's exceptional discrimination capabilities combined with its ability to identify patients with higher mortality risks holds great promise for improving patient outcomes and enabling faster access to treatment."
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"In a large number of cases, diagnostic data are often missing or discordant, making HFpEF detection challenging. AI can enhance echocardiography capabilities to help practices overcome the cumbersome intricacy of diastolic assessment. It is particularly useful for clinical centers that lack the time, resources, or expertise to perform comprehensive, diagnostic-quality, assessments."
By streamlining the screening process for this complex clinical syndrome, EchoGo® Heart Failure paves the way for more patients to receive the care they need sooner, potentially preventing more severe outcomes, and reducing HFpEF's significant burden on patients and healthcare.
Ultromics remains committed to advancing AI technology to transform cardiovascular healthcare. The groundbreaking findings from this study underscore the company's dedication to empowering healthcare professionals with tools that overcome existing bottlenecks and enhance patient care.
About Ultromics
Ultromics is a pioneer in advanced heart failure detection. The ground-breaking platform, EchoGo ®, is transforming the way heart failure is diagnosed using artificial intelligence and cardiac ultrasound as a modality. The technology empowers clinicians to make precise, efficient, and accurate assessments of heart failure, leveraging the largest known heart disease outcomes dataset in echocardiography, accurately interpreting echocardiograms and predicting cardiac outcomes.
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