EchoGo Core

EchoGo Core is the automated solution for cardiovascular findings – calculating Ejection Fraction, Global Longitudinal Strain and Left Ventricular Volumes.
Information source: Vendor
Last updated: Jan. 22, 2022

General Information

Product name EchoGo Core
Company Ultromics
Subspeciality Cardiac
Modality Ultrasound
Disease targeted Cardiac disease
Key-features Ventricle volume analysis, ejection fraction, strain, worksheet generation
Suggested use During: interactive decision support (shows abnormalities/results only on demand), report suggestion
After: diagnosis verification
Without interference of a radiologist: AI-only diagnosis

Technical Specifications

Data characteristics
Population All resting echo indications in adults
Input Resting Echo
Input format DICOM
Output PDF Report
Output format PDF
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone third party application, Stand-alone webbased
Deployment Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis Automatically, right after the image acquisition
Processing time 10 - 60 seconds


Certified, Class I , MDD
FDA 510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE) 5.1. Intended Use Quantification of cardiovascular function from an echocardiogram. 5.2. Indication for Use EchoGo Core is intended to be used for the quantification and reporting of results of cardiovascular function to support physician diagnosis. EchoGo Core is indicated for use in adult populations.


Market presence
On market since 11-2019
Distribution channels Caption Health
Countries present (clinical, non-research use) 2
Paying clinical customers (institutes) 1
Research/test users (institutes) 3
Pricing model Pay-per-use, Subscription
Based on Number of analyses


Peer reviewed papers on performance

  • Automated Echocardiographic Detection of Severe Coronary Artery Disease Using Artificial Intelligence (read)

Non-peer reviewed papers on performance
Other relevant papers