Radify Triage
by Envisionit DeepAI
· Based in United Kingdom →
— AI-assisted triage for critical chest X-ray findings.
Contact for pricing
Regulatory Status Disclosed
Overview
Radify Triage by Envisionit DeepAI is an artificial intelligence-powered software designed to analyze adult chest X-rays to assist in clinical decision support and workflow prioritization.
The tool is primarily built for radiologists, emergency medicine physicians, and intensive care clinicians operating in high-volume or time-critical settings, such as emergency departments, intensive care units, and public health clinics. It is designed to identify and highlight critical pathologies, specifically triaging conditions like pneumothorax and pleural effusion, as well as detecting signs associated with pneumonia and tuberculosis.
In terms of clinical workflow integration, Radify Triage operates in the background, processing medical imaging data directly from PACS or RIS systems. It provides case-level outputs and alerts directly within the radiologist’s existing worklist, allowing clinicians to prioritize urgent scans and reduce the time to treatment for critical cases without requiring additional manual steps or clicks.
- Automated Prioritization: Automatically flags and escalates critical chest X-ray findings to the top of the reading queue.
- Pathology Detection: Identifies and highlights key thoracic abnormalities, including pneumothorax, pleural effusion, and infectious disease indicators.
- Seamless Integration: Works autonomously with existing PACS/RIS infrastructures to support point-of-care diagnostics and high-throughput screening environments.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-assisted chest X-ray analysis
- Triage and prioritization of critical findings (pneumothorax, pleural effusion)
- Rapid analysis (average of three seconds to alert)
- High accuracy in triaging pathologies
- Provides case-level output for PACS worklist prioritization
- Enhances efficiency in emergency rooms and ICUs
- Integrates into existing PACS/RIS workflows
- Supports cloud, on-premise, or hybrid deployment
Use Cases
- Prioritizing urgent chest X-rays in emergency rooms
- Prioritizing urgent chest X-rays in intensive care units
- Assisting medical professionals in rapid diagnosis and treatment
- Improving workflow efficiency in radiology departments
- Addressing radiologist scarcity by automating triage
What Physicians Need to Know
DICOM Support & Standards
Radify Triage accepts frontal chest X-ray images (AP and PA views) in DICOM format. The system is designed to integrate with DICOM-compatible PACS for image exchange and results.
PACS Integration Method
Chest X-rays are sent to Radify Triage via PACS for analysis. The software processes images and flags them within the PACS to enable worklist prioritization for suspected critical findings like pneumothorax and pleural effusion. It provides case-level output directly in the PACS.
Reading Room Workflow Impact
Radify Triage is an AI-assisted triage and notification software that helps prioritize urgent or life-threatening cases, such as pneumothorax and pleural effusion, at the top of the worklist. It aims to enhance the efficiency and effectiveness of medical professionals in emergency rooms and intensive care units by providing rapid prioritization. The system does not send proactive alerts directly to specialists, direct attention to specific image portions, or remove cases from the queue. Results are not intended for standalone clinical decision-making.
AI Model Architecture (deep learning approach)
Radify Triage utilizes Artificial Intelligence (AI) algorithms, specifically Deep Convolutional Neural Networks (DCNN), for image analysis. It leverages machine learning to recognize patterns in imaging, annotate pathologies, and indicate their severity and localization.
Processing Speed (per study)
The system provides alerts to healthcare professionals within an average of three seconds. It can process and prioritize over 2,000 images per minute.
FDA Clearance Pathway (510k/De Novo)
Radify Triage received 510(k) clearance from the U.S. Food and Drug Administration (FDA) (K231871) for triaging pneumothorax and pleural effusion.
Supported Modalities (CT/MRI/X-ray/US)
The Radify Triage system is specifically an AI-assisted chest X-ray solution. It analyzes adult frontal chest X-ray images (AP and PA views) for pre-specified critical findings. Other Radify products from Envisionit Deep AI support mammograms and ultrasound, but Radify Triage focuses on chest X-rays.
Sensitivity & Specificity Data
Radify Triage demonstrated high accuracy in triaging both pneumothorax and pleural effusion. The device's performance was validated by clinical tests, showing > 95% AUC (Area Under the Curve). It was evaluated using diverse data and subgroup analysis to mitigate potential biases.
RSNA/ACR Validation
While specific RSNA/ACR validation is not mentioned, the system underwent thorough evaluation using diverse data and subgroup analysis through Envisionit's proprietary validation platform, Ratify. Ratify is designed to ensure robust, accurate diagnostic recommendations and meet rigorous FDA standards.
Physician Tip
Radify Triage is a powerful tool for rapidly prioritizing critical chest X-ray findings like pneumothorax and pleural effusion, especially in high-volume or emergency settings. Remember that it's a triage and notification system, not a standalone diagnostic tool; clinical decision-making still requires full radiologist interpretation. Leverage its speed to optimize workflow and ensure timely attention to urgent cases, but always review the full study. The system's ability to highlight and localize pathologies can also be a valuable aid in interpretation.
Radify Triage integrates seamlessly into existing radiology workflows by accepting DICOM-formatted chest X-rays directly from PACS. It provides case-level output back to the PACS for worklist prioritization, ensuring minimal disruption to current systems. As a software-only device, its integration focuses on data exchange standards and adherence to robust cybersecurity measures, which were a key part of its FDA clearance process. Organizations should ensure their PACS environment is compatible with DICOM standards for optimal integration.
Details
| Category | Radiology & Imaging AI, Triage & ER/ICU AI |
| Pricing | Contact for pricing |
| Deployment | Cloud, On-premise, Hybrid |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated 510(k) clearance (K231871) was received on January 17, 2024, for triaging pneumothorax and pleural effusion from adult chest X-ray images. |
| Integrations | |
| EHR | Not specified |
| Specialties | Critical Care, Emergency Medicine, Radiology |
Ratings & Reviews
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Press & Coverage
vertexaisearch.cloud.google.com
Radify Triage | FDA Radiology AI Device - X-ray Interpreter
Radify Triage is an AI-powered software by Envisionit DeepAI Ltd. that analyzes adult chest X-ray images to detect critical findings like pleural effusion and pneumothorax. It received FDA 510(k) clearance on January 17, 2024.
2024-01
FDA
K231871 - 510(k) Premarket Notification - FDA
This is the official FDA 510(k) Premarket Notification for Radify Triage, submitted by Envisionit Deepai, Ltd. The document details the regulatory information and classification for the device.
2026-06
HealthAidb
RADIFY Triage - HealthAidb u2014 Software
RADIFY Triage is an AI-powered software by Envisionit Deep AI designed to help radiologists quickly identify critical findings in chest X-rays, such as pneumothorax and pleural effusion. It provides rapid notifications within the PACS system to prioritize urgent cases and has received FDA 510(k) clearance.
2025-10
MDPI
Machine Learning-Enabled Medical Devices Authorized by the US Food and Drug Administration in 2024: Regulatory Characteristics, Predicate Lineage, and Transparency Reporting - MDPI
This article discusses the regulatory landscape of AI/ML-enabled medical devices authorized by the FDA in 2024, including Radify Triage (K231871) for chest X-ray triage for lung conditions. It highlights that radiology dominated device approvals and most were cleared via the 510(k) pathway.
2025-12
Innolitics
Definitive Guide to AI/ML SaMD Ground Truthing - Innolitics
This guide references Radify Triage (K231871) in the context of establishing 'ground truth' for AI/ML SaMD, noting that its ground truth was established by three board-certified ABR (USA) radiologists with a minimum of 11 years of experience.
2025-09
Innolitics
Command Line as a Medical Device (CLaMD) - Innolitics
Radify Triage is mentioned as an example of a Command Line as a Medical Device (CLaMD), where the software provides case-level output to PACS for worklist prioritization or triage, integrating with existing systems rather than having its own distinct user interface.
2025-05
unknown
Applications of AI/ML in accelerating the development of pulmonary drug delivery system
This review article lists Radify Triage (K231871) by Envisionit DeepAI Ltd. as an FDA-approved AI/ML-enabled device for detecting pleural effusion and pneumothorax from chest X-rays, with an approval date of January 17, 2024.
2024-01
unknown
K232365 - 510(k) Commentary
This commentary mentions Radify Triage in the context of cybersecurity and FDA AI request responses, highlighting its relevance to rigorous documentation for connected software-driven devices.
unknown
Videos
Product demos, reviews, and walkthroughs for Radify Triage.
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Frequently Asked Questions
Radify Triage is a radiological computer-assisted triage and notification software designed to analyze adult chest X-ray images. It provides case-level output directly in the Picture Archiving and Communication System (PACS) for worklist prioritization, without altering the existing reading queue. This integration helps flag images for urgent review by qualified medical specialists.
Radify Triage has received FDA clearance specifically for triaging Pneumothorax and Pleural Effusion, which are critical findings in emergency and intensive care settings. Beyond these, it can detect between 16 and 20 major abnormalities on chest X-rays, including patterns associated with Tuberculosis and pneumonia-related opacities.
Radify Triage has secured 510(k) FDA clearance for its ability to triage Pneumothorax and Pleural Effusion. This rigorous regulatory process involved extensive clinical testing and evaluations, confirming the device's adherence to high standards of accuracy, safety, and robust cybersecurity protocols.
The company behind Radify Triage emphasizes its commitment to ethical AI principles and underwent a meticulous evaluation against the FDA's robust cybersecurity standards during its 510(k) clearance. While specific technical details are not fully disclosed, healthcare AI solutions generally require robust encryption, access controls, and audit trails to ensure patient data privacy and security.
In the broader landscape of AI-powered medical imaging and triage, alternatives include solutions like Viz.ai for care coordination, BioCam for capsule endoscopy, and EIRL for medical image diagnosis support. Other AI triage systems such as ERTRIAGEu2122 focus on emergency department workflows, and various symptom-checker or digital triage platforms also exist.
Specific pricing for Radify Triage is not publicly available in the search results. However, the cost of implementing AI in healthcare varies significantly, with diagnostic AI systems in radiology typically ranging from $50,000 to $300,000. Enterprise-level integrations can exceed $300,000, with overall costs influenced by solution complexity, data readiness, and integration requirements.
Radify Triage is designed to assist healthcare professionals by prioritizing critical cases and enhancing efficiency, not to replace human clinical judgment. The company states it mitigates potential biases through thorough evaluation with diverse data. However, AI in triage generally faces limitations such as potential algorithmic bias if training data is not representative, and some AI systems may struggle with nuanced or complex cases requiring subtle clinical judgment.
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| Last Verified: 2026-04-18 | First Added: 2026-04-18