VUNO Med®-Chest X-ray™

Key Features

  • Abnormality detection

General Information

Product name

VUNO Med®-Chest X-ray™

Company

Subspeciality

Chest

Modality

X-ray

Disease targeted

Nodule/Mass, Consolidation, Interstitial Opacity, Pneumothorax, Pleural Effusion

Main task

Not specified

Technical Specifications

Population

All population with a risk of thoracic abnormalities

Patient population age

Not specified

Input

Chest XR PA/AP images

Input format

DICOM

Output

Abnormality score, Lesion heatmap, Lesion boundary

Output format

DICOM, GSPS

Integration

Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone third party application, Stand-alone webbased

Deployment

Cloud-based, Hybrid solution, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker)

Trigger for analysis

Automatically, Right after the image acquisition

Processing time

< 3 sec

Regulatory Information

CE Certification

Pathway:

MDD

Class:

Class IIa

Verified by Health AI Register
FDA Certification

Pathway:

510(k) cleared

Class:

Class II

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

06-2020

AI Platforms

Tempus

Resellers

Samsung Electronics

Countries present

10+

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Pay-per-use, Subscription

Based on

Number of analyses

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction

Peer-Reviewed

View

The diagnostic performance and clinical value of deep learning-based nodule detection system concerning influence of location of pulmonary nodule

Peer-Reviewed

View

Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings

Peer-Reviewed

View

Added Value of Deep Learning–based Detection System for Multiple Major Findings on Chest Radiographs: A Randomized Crossover Study

Other Articles

Other

View

Deep Learning-Based Automatic Chest PA Screening System for Various Devices and Hospitals, RSNA 2018

Other

View

Deep Learning-Based Computer-Aided Detection System for Multiclass Multiple Lesions on Chest Radiographs: Observers’ Performance Study, RSNA 2018

Other

View

Evaluation of the Performance of Deep Learning Models Trained on a Combination of Major Abnormal Patterns on Chest Radiographs for Major Chest Diseases at International Multi-centers, RSNA 2019

Source: vendor | First published: Jan 15, 2024 | Last updated: Jul 9, 2025