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Ultromics

Ultromics is an FDA-cleared, cloud-native medical imaging platform that uses deep learning and outcome-trained algorithms to automate echocardiogram analysis, specialized function tracking,...

Stop treating inconclusive diastolic readings like an unsolvable puzzle. Let breakthrough deep learning expose HFpEF with 90% sensitivity.

Stop treating inconclusive diastolic readings like an unsolvable puzzle. Let breakthrough deep learning expose HFpEF with 90% sensitivity.

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Echocardiography AIFDA BreakthroughHFpEF DetectionAmyloidosis ScreeningPACS Integration
9.4 Zekai
Best in category
AI for Doctors & Medical
Ease of Use
4.4
Accuracy
4.9
Value
4.6
Time Saving
4.8
Leading global health networksUsers
9.4/10Zekai Score
How It Works

Your workflow, automated

1
Route echo clip
Send a standard routine echocardiography DICOM clip natively to the secure cloud server via automated background workflows.
2
Deep pixel processing
The platform's deep learning core analyzes frame sequences, mapping structural properties and myocardial strain benchmarks in the background.
3
Review structural report
Open your native reading workstation monitor to evaluate clear probability scores and precise, structured diagnostic indices.
Ready to automate your workflow with Ultromics?
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Real Impact

Before & After

❌ Before

Missing subtle signs of Heart Failure with Preserved Ejection Fraction (HFpEF) or waiting across five separate specialist visits to finally uncover cardiac amyloidosis.

64% indeterminate classifications
✅ After

Automated, cloud-based pattern recognition that delivers definitive probability scoring and risk stratification back to your PACS.

Under 20-minute reports
Social Proof

Trusted by Leading global health networks

Leading global health networks professionals using this tool
Ease of Use
4.4
Accuracy
4.9
Value
4.6
Time Saving
4.8

""

This cloud post-processing platform has completely revolutionized our cardiac imaging read rotations. Moving past indeterminate diastolic scores to explicit probability numbers lets us treat complex heart conditions confidently.

""

The automated global longitudinal strain (GLS) and volume calculations are fantastic. It eliminates operator variability completely, dropping structured reports directly into our PACS dashboard tables in minutes.

""

Outstanding diagnostic depth for preventative cardiology and failure sub-type tracking. The clinical evidence files are pristine, though coordinating secure cloud VPN connections across hospital servers takes clear IT focus.

""

Saves our multi-campus provider network massive amounts of documentation and review stress every week. The outpatient billing paths run smoothly under dedicated codes, keeping our shared savings tracking highly profitable.
Leading global health networks+ professionals are already using this tool.
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Connects With

Works with your existing stack

Epic Oracle Cerner Change Healthcare PACS Philips PACS GE Centricity
Setup complexity: Technical configuration required
Ultromics is an FDA-cleared, cloud-native medical imaging platform that uses deep learning and outcome-trained algorithms to automate echocardiogram analysis, specialized function tracking, and early heart failure detection.
Who It's For

Why Doctors & Medical choose this tool

🎯
Built for
Cardiologists seeking automated, objective heart failure phenotyping and strain analysis from routine echo clips
In-Depth Overview
Ultromics splits its computational algorithms across dedicated, FDA-cleared breakthroughs—specifically EchoGo Heart Failure for continuous HFpEF probability mapping and EchoGo Amyloidosis for automated structural tracking. The platform evaluates sequences of echocardiogram frames concurrently, using networks trained on over a decade of verified outcomes to extract underlying patterns that remain completely invisible to the human eye. By bypassing traditional binary score thresholds in favor of a granular continuous risk score, it minimizes diagnostic uncertainty. For enterprise cardiology networks, this cloud workflow removes manual scripting and button-clicking delays entirely. When a local sonographer saves a routine apical 4-chamber ultrasound file, the automated DICOM pipeline routes the file securely to the SaaS model, computes ventricular volumes, and returns color-coded analytical summaries in under twenty minutes. This automated tracking loop helps primary care teams connect vulnerable cohorts with targeted therapeutics before acute hospitalization loops trigger. This ecosystem scales safely across diverse healthcare infrastructure networks by utilizing a hardware-agnostic design that works with any ultrasound hardware manufacturer. It provides financial validation metrics through established, active insurance billing tracks—including direct CMS outpatient pass-through reimbursements and specialized inpatient DRG add-on codes. One honest operational reality to keep in mind relates to the cloud transit pipeline. Because the engine runs comprehensive, multi-layer computational fluid and structural analyses to guarantee high specificity benchmarks, reports are delivered asynchronously in short windows rather than popping up instantly on screen, requiring you to map study review queues intentionally around your shift routines.

Key Use Cases

🫀
Resolve indeterminate HFpEF cases
Echocardiography Cardiologist
Utilize deep learning continuous probability scores to differentiate complex heart failure sub-types confidently.
33% better patient management
🔬
Screen for cardiac amyloidosis
Clinical Trial Coordinator
Deploy automated systematic screening across incoming echo data logs to catch rare infiltrative conditions early.
0.93 AUC diagnostic accuracy
🏥
Maximize department throughput
Cardiology Service Lead
Automate routine volume and global longitudinal strain calculations to clear out dense sonographer piles.
25% shift study time saved
✓ Pros
Reduces diagnostic uncertainty by resolving up to ninety percent of traditional indeterminate classifications
Saves up to twenty-five percent of overall echocardiography reading time by automating strain lookups
Natively integrates within existing PACS workflows via secure, background DICOM pipelines
Eligible for direct Medicare reimbursement codes averaging $280+ in outpatient clinical settings
Grounded in real-world validation datasets built in partnership with the Mayo Clinic and Oxford University
· Cons
Requires stable internet connectivity to transport large DICOM clips to cloud servers safely
Processing pipelines average twenty minutes per report, preventing instantaneous bedside feedback loops
Requires professional human integration to combine continuous risk scores with active physical parameters
Questions & Answers

Frequently asked questions

How does EchoGo Heart Failure outperform traditional clinical scoring systems? +
Traditional models like H2FPEF leave up to 64% of patients in an 'indeterminate' gray zone. EchoGo uses outcomes-driven deep learning to reduce indeterminate classifications to just 7%, delivering clear, actionable results for over 80% of patients.
Is Ultromics hardware dependent on a specific ultrasound machine manufacturer? +
No. The platform is entirely vendor-agnostic and cloud-native. It connects with any standard digital ultrasound hardware format in any care setting, parsing DICOM files cleanly behind the scenes.
Are there specific billing codes available for this AI echocardiography tool? +
Yes. In outpatient environments, the platform is reimbursable under Medicare average codes (HCPCS C9786) providing around $284 per analysis. Inpatient settings leverage dedicated NTAP ICD-10 codes.
Does patient data privacy meet enterprise medical tracking rules? +
Yes. The platform utilizes a secure SaaS framework compliant with HIPAA and SOC 2 Type 2 rules. Patient identifiers are fully anonymized and encrypted in transit and at rest before cloud processing executes.
Doctors & Medical

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