Heart Failure Uncovered
EchoGo® is clinically proven AI that helps diagnose challenging cardiac diseases by analyzing routine echocardiograms.
Breakthrough Technology
Improved diagnostic accuracy and classification
Achieving a new standard of care in diagnostic precision.
Automated reports to support clinical decisions
Reports delivered in under 20 minutes.
“This novel solution applies AI to cardiovascular imaging to greatly simplify identification of patients with HFpEF, a diagnosis that can be challenging to make, and allow more expeditious treatment.”
The EchoGo® platform
The EchoGo® platform operates seamlessly in the background, running Ultromics’ advanced algorithms at scale. Designed to integrate effortlessly into your workflow, EchoGo® connects with your existing infrastructure and provides seamless access to reports.
Integrate Seamlessly
- Easily implemented, with no hardware/software at site.
- Integrates with existing workflows and IT stacks.
- Secure cloud VPN connection and data anonymized.
Analyze Data
- EchoGo® analyzes data, identifies suspected findings, and generates a report.
- A report is sent to PACS for the interpreting physician.
- Operates in an automated DICOM workflow.
Get Reimbursed
- Inpatient: NTAP Code ICD-10 XXE2X19 – $1,000 per analysis (Medicare-covered).
- Outpatient: HCPCS Code C9786, Clinical APC Code 574 – $285 per analysis (covered by Medicare and select commercial insurers).
Scale with Ease
- Deploy Ultromics’ AI algorithms across any care setting—from hospitals to clinics—without workflow disruption.
- Minimal training to onboard new staff with ease.
Working with global leaders to deliver
transformative outcomes
Each of our partners are innovation leaders are working with us to improve care. We partner with exceptional leaders across all stages to build transformative technologies.
Perspectives from leading experts
Latest research and innovation
Our FDA-cleared modules
Ultromics' algorithms are trained on 10 years of outcome data to reliably recognize suspicious echocardiograms. The algorithms automatically analyzes studies, identifies disease, and provides clinicians with clear, actionable assessments, alerting them to potential findings. Recognized for its transformative impact, the technology has received Breakthrough Device Designation and clearance by the FDA.
Up to 64% of HFpEF patients may be undiagnosed2
Proven to detect HFpEF with
90% sensitivity and 86% specificity1
Cardiac amyloidosis typically requires patients to have 5 or more medical visits before a diagnosis is made.
Proven to detect CA with 84.5% sensitivity and 89.7% specificity.
“Novel AI-based diagnostic tools such as EchoGo® Amyloidosis from Ultromics should help facilitate disease identification, particularly in clinics and hospitals restricted by expertise and resource. ”
Leading innovation with scientific excellence and clinical validation
We are redefining heart failure as we know it
Innovation is at the heart of everything we do
At the heart of our mission is a commitment to making heart failure detection easier for providers and prognosis better for patients. Healthcare professionals should receive critical information they need minimizing the added risks and costs of untreated patients or further procedures. Staying true to the standards set by our Oxford University origins, we are partnering with the most trusted and validated medical organizations in the world to improve quality of life and reduce the burden on the healthcare system at large.
“The FNIH will harness valuable perspectives and expertise of a select number of collaborations, including Ultromics, to alleviate this unmet need and pave the way for better classification and more precise treatment strategies.”
[1] Gerber Y, Weston SA, Redfield MM, et al. A contemporary appraisal of the heart failure epidemic in Olmsted County, Minnesota, 2000 to 2010. JAMA Internal Medicine. 2015;175:996–1004. [2] Savarese G and Lund LH. Global public health burden of heart failure. Cardiac Failure Review. 2017;3:1:7-11. [3] Borlaug, BA, Sharma K, Shah SJ, et al. Heart failure with preserved ejection fraction, :JACC Scientific Statement. Journal of the American College of Cardiology. 2023;81:1810–1834. [4] Akerman AP, Porumb M, Beqiri A, et al. Comparison of clinical algorithms and artificial intelligence applied to an echocardiogram to categorize risk of heart failure with preserved ejection fraction. Journal of the American College of Cardiology. ACC. 2023;81 (8_Supplement) 360.
Curious about how Ultromics can support your facility?
Request a meeting with us to learn more