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EchoGo Pro provides reports to support physicians in the treatment of patients with suspected coronary artery disease. Through specialized image based machine learning, EchoGo Pro assists physicians identify heart disease risk rapidly to enable appropriate care.
The EchoGo Pro module can be added onto the EchoGo platform in the United Kingdom and Europe. Coming soon to the United States.
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Accurate and fast analysis to enable physicians at any skill level to feel confident in making diagnostic recommendations to patients. Full automation reduces variability.
Identifies indications of ischemia (CAD) with increased sensitivity, helping to detect early signs and enable preventative steps before a heart attack strikes, ultimately saving lives.
Allows improved identification of at-risk individuals to be treated quickly – and those not at risk to be spared from unnecessary tests, surgery and treatment.
The system is zero click. Echocardiograms are automatically sent to Ultromics for analysis and a report is returned within minutes.
EchoGo Pro was trialed in the UK and US and achieved a diagnostic performance of over 90% (AUROC), significantly reducing the number of misdiagnoses compared to reports of routine clinical practice. The technology has been validated and developed through its partnership in the EVAREST trial with the NHS, one of the largest ultrasound programmes in the world. It’s trained on past clinical examples, to spot thousands of features, compared to a handful of indicators in traditional visual inspection. The EVAREST validation trial continues to run in over 30 NHS hospitals and has recruited over 6000 patients to date.
EchoGo Pro uses novel features derived from Stress Echo images and machine learning algorithms. The system was tested on an independent validation dataset demonstrating an area under the ROC curve of 0.927.
In a reader study to evaluate the benefit of EchoGo Pro in clinical settings, clinicians performed significantly better by diagnostic accuracy, with the aid of EchoGo Pro.
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Get started with zero up front costs
