supports cardiovascular disease diagnostics by providing machine learning based solutions that analyze and interpret echocardiograms, which are ultrasound images of the heart, creating patient reports, at scale, on mobile, on premises and cloud-based platforms.
Product specifications Information source: Vendor
Last updated: April 5, 2023
Product name Us2.v1
Subspeciality Cardiac
Modality Ultrasound
Disease targeted Heart disease, Pulmonary Hypertension
Key-features Automated measurements include 2-dimensional (cardiac volumes, all 4 chambers of the heart), M-mode (e.g. tricuspid annular plane systolic excursion), spectral Doppler (blood flow across all valves, both PW and CW measurements) and tissue Doppler
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), report suggestion
Data characteristics
Population Vast majority of adult transthoracic echocardiograms. Not intended for reporting measurements associated with valve disease, pericardial disease, or right-sided hemodynamics (e.g. estimated pulmonary artery systolic pressure); intra-cardiac lesions (e.g. tumours, thrombi); and will not report measurements for complex adult congenital heart disease.
Input Transthoracic echocardiography
Input format DICOM
Output Patient report, editable image annotations, comparison to international reference guidelines
Output format DICOM SR, PDF, CSV
Integration Integration in standard reading environment (PACS), Integration CIS (Clinical Information System), Integration via AI marketplace or distribution platform, Stand-alone third party application, Stand-alone webbased
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based, Hybrid solution
Trigger for analysis Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time 1 - 10 minutes
Certified, Class IIb , MDR
510(k) cleared, Class II
Market presence
On market since 06-2022
Distribution channels Blackford, Aidoc aiOS, Viz Platform, Eureka Clinical AI, Nuance PIN
Countries present (clinical, non-research use) USA, Canada, EU, Australia, New Zealand, Singapore
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Subscription
Based on Number of analyses
Peer reviewed papers on performance

  • A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram (read)

  • Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study (read)

Non-peer reviewed papers on performance
Other relevant papers

  • Democratizing Echocardiography with Augmented Intelligence (read)