VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage
Regulatory Status Disclosed
Overview
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is an AI-based software solution designed to analyze adult chest X-ray images for the rapid detection of critical conditions such as pleural effusion and pneumothorax. This radiological computer-assisted triage and notification software utilizes a convolutional neural network (CNN) based deep learning algorithm to identify features suggestive of these critical findings. It provides case-level output for worklist prioritization or triage within a radiologist’s PACS or workstation, delivering passive notifications without marking the original images. The software is intended to assist healthcare professionals in managing urgent cases efficiently by providing rapid automated classification results, contributing to faster treatment in emergency rooms and other medical settings. It supports DICOM, JPG, and PNG image formats and is designed to integrate seamlessly into standard reading environments. The device achieved high performance with ROC AUC > 0.95 and sensitivity/specificity above 95% for both conditions, with notification timing under 10 seconds.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-based analysis of adult chest X-ray images
- Detection of pleural effusion and pneumothorax
- Prioritizes urgent cases in clinical workflow
- Provides passive notifications in PACS/workstation
- Supports DICOM, JPG, and PNG image formats
- Utilizes Convolutional Neural Network (CNN) based deep learning algorithm
- High diagnostic performance (ROC AUC > 0.95, sensitivity/specificity > 95%)
- Rapid notification timing (under 10 seconds)
- Vendor agnostic algorithm
- Integration with PACS and EMR systems
Use Cases
- Rapid screening for critical conditions in emergency rooms
- Prioritizing radiologist worklists for urgent cases
- Assisting healthcare providers in efficient case management
- Diagnostic support for major pulmonary diseases
- Reducing chest X-ray reading time
- Improving accuracy of X-ray interpretations
What Physicians Need to Know
DICOM Support & Standards
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage uses DICOM (Digital Imaging and Communications in Medicine) standards to analyze chest X-ray images. It is compatible with DICOM chest X-ray images and can receive transmitted images from medical imaging devices via SCP communication and send/store analyzed images to servers with PACS and SCP communication through SCU communication.
PACS Integration Method
The tool provides case-level output available in the PACS/workstation for worklist prioritization or triage. It can be interfaced with PACS and offers integration in a standard reading environment, via an AI marketplace or distribution platform, or as a stand-alone web-based or third-party application. It can also be deployed as a cloud-based, hybrid, or locally virtualized solution.
Reading Room Workflow Impact
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is designed to assist healthcare professionals in making diagnostic decisions by detecting abnormalities on chest radiographs, aiming to reduce reading time and improve diagnostic accuracy. Studies have shown it can cut reading time by approximately 50% and improve diagnostic accuracy across various experience levels of assessors. It provides instant and visualized results with a colored heatmap. The software provides case-level output for worklist prioritization and triage, acting as a passive notification tool rather than sending proactive alerts.
AI Model Architecture (deep learning approach)
The algorithm is based on a convolutional neural network (CNN), a deep learning technology that learns features from data. It was trained on chest X-ray data from medical centers across South Korea and India, including images from over 13 different modality manufacturers.
Processing Speed (per study)
The average time for displaying results is 7.86 seconds, with some reports indicating analysis of abnormalities in as little as 3 seconds.
FDA Clearance Pathway (510k/De Novo)
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage received FDA 510(k) clearance (K241439) on November 15, 2024, as a Class II radiological computer-assisted prioritization software for lesions (product code QFM).
Supported Modalities
The tool supports chest X-ray (PA/AP) images. It is designed to analyze adult chest X-ray images. While the primary focus is X-ray, Vuno also offers solutions for CT modalities.
Sensitivity & Specificity Data
Clinical studies have shown that the diagnostic accuracy, including per-lesion and per-image sensitivity, improved significantly with the use of VUNO Med-Chest X-ray. The accuracy of classification performance is equivalent to the predicate device, with both Pneumothorax and Pleural Effusion exceeding an ROC AUC of 0.95. For multiclass lesion detection, the CAD software achieved a JAFROC FOM of 0.943 compared to an average of 0.851 for radiologists (P < 0.001). For image-wise classification of normality/abnormality, the CAD software achieved an AUROC of 0.985 (with a high specificity of 99.9%) compared to an average of 0.958 for radiologists (P = 0.001). In a study evaluating detection of suspicious pulmonary nodules, the AI system achieved a sensitivity of 85.2%.
RSNA/ACR Validation
VUNO has presented research related to its deep learning-based chest X-ray screening system at RSNA (Radiological Society of North America) in 2018 and 2019.
Physician Tip
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is a valuable tool for prioritizing chest X-ray readings, especially in high-volume settings like emergency rooms, by quickly identifying suspected critical findings such as pleural effusion and pneumothorax. The AI provides case-level output for worklist prioritization, but it's crucial to remember that it's a passive notification tool and does not replace the radiologist's final interpretation. The visualized results with colored heatmaps can be particularly helpful for rapid assessment. While it significantly reduces reading time and improves diagnostic accuracy, the final clinical decision should always be made by a trained radiologist or healthcare professional.
The VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is designed for flexible integration into existing clinical workflows. It supports DICOM standards for seamless image transfer and can be interfaced with PACS. Deployment options include integration within a standard reading environment, via AI marketplaces, as a stand-alone application (web-based or third-party), or embedded directly into X-ray devices. It can be deployed as a cloud-based, hybrid, or locally virtualized solution, and offers APIs for customized integration into user reading systems.
Details
| Category | Radiology & Imaging AI, Triage & ER/ICU AI |
| Pricing | Unknown |
| Deployment | Cloud-based, Hybrid solution, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker). It integrates with PACS and can be interfaced with PACS (Picture Archiving and Communication System) and other radiological imaging equipment. |
| Mobile App | VUNO Med-Chest X-ray is embedded on Samsung's GM85 mobile x-ray system. |
| API Available | Unknown |
| Data Export | Unknown |
| Compliance | |
| BAA Available | Unknown |
| HIPAA Compliant | Unknown |
| FDA Status | Cleared AI-estimated |
| Integrations | |
| EHR | Not specified |
| Specialties | Critical Care, Emergency Medicine, Radiology |
What the Web Says
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is an AI-powered solution designed to assist healthcare providers in rapidly screening chest X-ray images for critical findings like pneumothorax and pleural effusion. The system aims to provide quick, automated classification results to facilitate faster treatment, especially in emergency settings. It has received FDA 510(k) clearance and CE Mark approval, indicating its compliance with regulatory standards in the US and Europe.
Overall: PositiveStrengths
- Rapid automated classification of critical findings, contributing to faster treatment in emergency rooms.
- Improved diagnostic accuracy and reduced reading time for medical staff (by an average of 50%).
- Useful diagnostic support tool for clinicians of varying experience levels.
- Ability to detect and localize major abnormal findings like nodules/mass, consolidation, interstitial opacity, pneumothorax, and pleural effusion.
- Can be integrated into various clinical workflows, including PACS, cloud-based services, and embedded into X-ray devices.
- Offers an intuitive user interface and optimized services, including APIs for seamless integration.
Limitations
- Not intended to direct attention to specific portions of an image or anomalies other than pleural effusion and/or pneumothorax.
- Results are not intended to be used on a stand-alone basis for clinical decision-making.
- As a passive notification tool, it does not send proactive alerts directly to medical specialists.
- Limited information available from independent physician reviews on platforms like Reddit, G2, or Capterra specifically for this product, making it difficult to gauge widespread user sentiment outside of official studies and press releases.
Based on reviews from: Korea Biomedical Review, VUNO (vuno.co), Health AI Register, accessdata.fda.gov, AuntMinnie, Axtech, KoreaTechToday, App Commons, AI Device Index, Capterra, Reddit
Last updated: 2026-10-23
Ratings & Reviews
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Press & Coverage
Korea Biomedical Review
VUNO's AI-driven chest X-ray triage solution scores FDA nod - Korea Biomedical Review
VUNO announced on November 20, 2024, that its AI-based chest X-ray reading assistant solution, VUNO Med-Chest X-ray Triage, received 510(k) Clearance from the U.S. FDA. The solution rapidly screens for pneumothorax and pleural effusion in chest X-ray images, aiming to provide faster treatment in emergency settings.
2024-11
코메디닷컴
FDA Approved VUNO's AI Chest X-ray Diagnostic Device - 코메디닷컴
On November 19, 2024, VUNO announced that its AI-based chest X-ray diagnostic device, VUNO Med-Chest X-ray Triage, received FDA approval. This AI solution analyzes chest X-ray images to quickly detect and categorize conditions like pneumothorax and pleural effusion, aiming to accelerate global expansion.
2024-11
AI Device Index
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage by Vuno Inc. - AI Device Index
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage was cleared by the FDA through 510(k) on November 15, 2024, under submission K241439. It is classified as a Class II radiological computer-assisted prioritization software for lesions.
2024-11
FDA
K241439 - 510(k) Premarket Notification - FDA
The FDA's 510(k) Premarket Notification for VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage, dated November 15, 2024, details its classification as a radiological computer-assisted triage and notification software. The device analyzes adult chest X-ray images for suspected critical findings like pleural effusion and/or pneumothorax.
2024-11
Korea Biomedical Review
VUNO to showcase FDA-cleared AI solutions at RSNA 2024 - Korea Biomedical Review
VUNO announced on November 28, 2024, its plans to promote its FDA-cleared VUNO Med-Chest X-ray Triage at RSNA 2024. This AI solution detects pneumothorax and pleural effusion in chest X-rays and will be a key focus for VUNO's expansion into overseas markets.
2024-11
Signify Research
AI in Medical Imaging News Round Up – November 2024 | Signify Research
A November 2024 news roundup highlights VUNO Inc. receiving FDA clearance for VUNO Med–Chest X-ray Triage, a solution for the detection of pneumothorax and pleural effusion. This was among several regulatory approvals in the medical imaging AI space.
2024-12
Korea Biomedical Review
VUNO to issue $18 mil. in bonds for US expansion, R&D - Korea Biomedical Review
VUNO announced on December 24, 2024, its plan to issue $17.9 million in perpetual convertible bonds to fund global business expansion, particularly in the U.S. market, following FDA approvals for VUNO Med-DeepBrain and VUNO Med-Chest X-ray Triage.
2024-12
RadAIslice
VUNO | Radiology AI Companies
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage, released on November 15, 2024, is an FDA-regulated AI-based software that analyzes adult chest X-rays to detect critical conditions like pleural effusion and pneumothorax, prioritizing urgent cases in the clinical workflow.
2024-11
Videos
Product demos, reviews, and walkthroughs for VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage.
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Frequently Asked Questions
VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is an AI-powered radiological computer-assisted triage and notification software. It analyzes adult chest X-ray images to detect pre-specified suspected critical findings, specifically pleural effusion and pneumothorax. The primary use is to prioritize worklists in PACS/workstations, helping healthcare providers accelerate the identification of urgent cases for faster treatment, especially in settings like emergency rooms.
Yes, VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage received FDA 510(k) clearance on November 15, 2024. It is classified as a Class II medical device under regulation 21 CFR 892.2080, with product code QFM, for radiological computer-aided triage and notification software.
The software is not intended to direct attention to specific portions of an image or anomalies other than pleural effusion and/or pneumothorax. Its results are not intended to be used on a stand-alone basis for clinical decision-making or direct diagnosis or treatment. The final diagnosis and treatment decisions must be made by trained radiologists or healthcare professionals.
The software uses an artificial intelligence algorithm to analyze images and provides case-level output available in the PACS/workstation for worklist prioritization or triage. It is compatible with DICOM chest X-ray images and can receive transmitted images from medical imaging devices, interfacing with Picture Archiving and Communication Systems (PACS) using the DICOM protocol.
Yes, several FDA-cleared AI solutions exist for chest X-ray triage, including Lunit INSIGHT CXR Triage, Gleamer ChestView, and Annalise.ai CXR. VUNO Med-Chest X-ray Triage focuses on rapidly screening for pneumothorax and pleural effusion to prioritize urgent cases. While specific comparative performance metrics against all alternatives are not detailed, studies have shown VUNO Med-Chest X-ray to improve diagnostic accuracy and reduce reading time.
The AI algorithm was trained on data sourced from four distinct sites in South Korea and India, including medical imaging centers, data partners, and medical hospitals, using images from over 13 different modality manufacturers. A 'locked' algorithm is used, meaning the same input will consistently produce the same results.
The device is intended to assist healthcare professionals in making diagnostic decisions by detecting abnormalities on chest radiographs, potentially reducing clinical effort, reading time, and fatigue. By providing rapid automated classification results, it can contribute to faster treatment in emergency rooms and other medical settings, indirectly benefiting patients through improved accuracy and speed of diagnosis.
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| Last Verified: 2026-04-19 | First Added: 2026-04-19