DrAid for Radiology v1
by VinBrain Joint Stock Company
· Based in Vietnam →
— AI-powered assistant for diagnostic radiology
Contact for pricing
Regulatory Status Disclosed
Overview
DrAid for Radiology v1 is an advanced AI-powered assistant developed by VinBrain Joint Stock Company to enhance diagnostic imaging workflows for radiologists. It leverages artificial intelligence algorithms to interpret and analyze medical imaging data, primarily focusing on chest X-rays. The tool is designed to aid in the clinical assessment of adult chest X-ray cases by identifying features suggestive of pneumothorax and other abnormalities, enabling prioritized review by medical specialists. DrAid aims to improve diagnostic accuracy, reduce image interpretation time, and streamline radiologists’ workflows, ultimately contributing to better patient outcomes. It supports comprehensive screening for various conditions, including lung, heart, and bone abnormalities, as well as assisting in the diagnosis and treatment of liver cancer and endemic diseases like tuberculosis and thalassemia. The platform can be deployed via a Software as a Service (SaaS) model or an on-premises appliance.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-enabled triage and notification for chest X-rays
- Detection of pneumothorax and other abnormalities
- Prioritization of time-sensitive findings in chest X-rays
- Assists in clinical management and reduces reporting errors or delays
- Screens for 21 lung, heart, and bone abnormalities
- High accuracy (e.g., 91% for chest X-rays, over 95% for liver cancer lesions)
- Reduces image interpretation time (up to 30%)
- Supports abdominal CT screening, cancer diagnosis and treatment
- Manages endemic diseases like tuberculosis and thalassemia
- Automated generation of intelligent medical reports (DrAid Enterprise Data Solution)
Use Cases
- Prioritizing and triaging abnormalities in chest X-rays
- Assisting radiologists in diagnosing lung, heart, and bone diseases from X-rays
- Screening and detection of liver cancer (CT Liver Cancer D&T)
- Screening for pervasive diseases including tuberculosis, thalassemia, and COVID-19
- Streamlining radiologists' workflows and reducing interpretation time
- Supporting diagnostic radiology as a second reader or assistant
What Physicians Need to Know
DICOM Support & Standards
DrAidu2122 for Radiology v1 processes chest X-ray images in DICOM format and can provide analysis results as DICOM files containing information on suspected pneumothorax.
PACS Integration Method
The tool integrates with PACS by automatically retrieving chest radiographs and making case-level output available for worklist prioritization or triage via an API service. VinBrain's platform is designed to store, connect, filter, and standardize medical data from HIS, RIS, and PACS.
Reading Room Workflow Impact
DrAidu2122 for Radiology v1 is a computer-assisted triage and notification software that works in parallel with the standard workflow to prioritize adult Chest X-Ray cases suggestive of pneumothorax. It does not alter the reading queue or provide diagnostic information directly. It can lead to a substantial 30% reduction in image interpretation time by intelligently prioritizing cases.
AI Model Architecture (deep learning approach)
DrAidu2122 analyzes cases using an artificial intelligence algorithm. VinBrain has developed over 300 AI models for medical image processing, utilizing a dataset of more than 2.5 million images.
Processing Speed (per study)
The average performance time for DrAidu2122 for Radiology v1 to analyze a study and send a notification to the PACS worklist is 3.83 minutes.
FDA Clearance Pathway (510k/De Novo)
DrAidu2122 for Radiology v1 received FDA 510(k) clearance as a Class II device (Regulation Number: 892.2080, Product Code: QFM). Its predicate device was HealthPNX (K190362) for Pneumothorax.
Supported Modalities
DrAidu2122 for Radiology v1 is specifically designed to aid in the clinical assessment of adult Chest X-Ray cases for features suggestive of pneumothorax.
Sensitivity & Specificity Data
For pneumothorax detection on chest X-rays, DrAidu2122 for Radiology v1 demonstrated a sensitivity of 93.15% (95% CI: 87.76-96.67) and a specificity of 92.99% (95% CI: 90.19-95.19), with an AUC of 98.3% (95% CI: 97.40-99.02).
RSNA/ACR Validation
The algorithm was validated using the NIH Public data set and an additional Vietnamese data set, with performance testing conducted in two separate pivotal studies. No explicit direct RSNA/ACR validation studies were found for this specific version.
Physician Tip
DrAidu2122 for Radiology v1 serves as an effective triage and notification tool for adult Chest X-Rays, specifically for suspected pneumothorax. Radiologists should integrate its output for worklist prioritization to potentially reduce interpretation time and manage workload more efficiently. Remember that the tool provides notification for prioritization and is not intended for standalone diagnostic decision-making or to direct attention to specific anomalies. Clinical assessment by a qualified medical specialist remains paramount.
DrAidu2122 for Radiology v1 is designed for seamless integration with existing PACS and other image storage systems via an API, providing results in DICOM format. This allows for automated retrieval of studies and notification for triage without disrupting the core PACS workflow. Consider its SaaS model for deployment.
Details
| Category | Radiology & Imaging AI |
| Pricing | Contact for pricing — Contact for pricing |
| Deployment | Cloud (SaaS), On-premise (Appliance), Hybrid |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated DrAid for Radiology v1 (K221241) received FDA 510(k) clearance on August 31, 2022, as a radiological computer-assisted triage and notification software for adult Chest X-Ray cases with features suggestive of pneumothorax. |
| Integrations | |
| EHR | Not specified |
| Specialties | Emergency Medicine, Pulmonology, Radiology |
Ratings & Reviews
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Press & Coverage
VinBrain Joint Stock Company
DrAid for Radiology v1
DrAid for Radiology v1 is an AI-enabled medical device for image analysis and processing, specifically designed for radiological computer-assisted triage and notification.
2022-09
U.S. Food & Drug Administration (FDA)
510(k) Premarket Notification - DrAid for Radiology v1 (K221241)
The FDA granted 510(k) clearance for DrAid for Radiology v1 on September 1, 2022, classifying it as a Class II radiological computer-aided triage and notification software.
2022-09
Innolitics
DrAid for Radiology v1 (K221241) u2014 FDA 510(k)
Innolitics provides details on the FDA 510(k) clearance for DrAid for Radiology v1, highlighting its role in AI/ML medical-device development and regulatory strategy.
2022-09
FDA.report
Radiological Computer-Assisted Prioritization Software For Lesions QFM
DrAid for Radiology v1 by VinBrain Joint Stock Company is listed among radiological computer-assisted prioritization software for lesions with product code QFM, cleared by the FDA in September 2022.
2022-09
Innolitics
Definitive Guide to AI/ML SaMD Ground Truthing
This article references DrAid for Radiology v1 (K221241) in the context of AI/ML SaMD ground truthing, noting that its dataset was reviewed by a panel of three US board-certified radiologists.
2025-09
National Library of Medicine (NIH)
Applications of AI/ML in accelerating the development of pulmonary drug delivery system
DrAid for Radiology v1 (K221241) is cited in a review of AI/ML applications in pulmonary drug delivery, specifically for its use in CXR analysis for pneumothorax.
2022-09
RadAI Slice
DrAidu2122 for Liver Segmentation | FDA Radiology AI Device - X-ray Interpreter
While primarily about DrAid for Liver Segmentation, this source also mentions DrAid for Radiology v1 with its 2022 510(k) clearance, indicating VinBrain's broader portfolio of AI radiology tools.
2022
U.S. Food & Drug Administration (FDA)
Records processed under FOIA Request 2023-8281
FDA records confirm the 510(k) submission and clearance of DrAid for Radiology v1, detailing its intended use as a radiological computer-assisted triage and notification software for adult Chest X-Ray cases suggestive of pneumothorax.
2024-05
Videos
Product demos, reviews, and walkthroughs for DrAid for Radiology v1.
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Frequently Asked Questions
DrAid for Radiology v1 is designed to assist medical staff by automatically classifying 21 common abnormalities related to lungs, heart, and bone from chest X-rays. It aims to streamline the diagnostic process, potentially saving 80-85% of initial screening time and increasing image reading accuracy by up to 25% when used in conjunction with a physician.
DrAid for Radiology v1 has received approval from the US Food and Drug Administration (FDA), making it the first and only AI product for X-ray Diagnostics in Viu1ec7t Nam and Southeast Asia to meet these standards. This approval legally permits its business and use in the United States, signifying its adherence to high quality and safety standards.
While DrAid for Radiology v1 offers significant assistance, it is an aid and not a replacement for human expertise, classifying 21 common abnormalities, which means it does not cover all possible conditions. Physicians should maintain oversight, as AI tools are supplementary and their reported accuracy of over 91.2% indicates it is not infallible.
Yes, the market includes several other AI-powered radiology solutions and platforms. Some alternatives include Aidoc, PowerScribe One, AZmed's Rayvolve products (AZtrauma, AZchest), and various PACS/RIS integrated AI tools from companies like Philips IntelliSpace PACS and Siemens syngo.via.
Specific pricing details for DrAid for Radiology v1 are not publicly available in the provided information. Generally, pricing for healthcare AI solutions can vary significantly based on factors such as the size of the healthcare facility, the volume of studies, integration requirements with existing PACS/RIS systems, and the scope of features implemented.
DrAid for Radiology v1 boasts an average reliability accuracy of more than 91.2% in automatically classifying 21 common abnormalities related to lungs, heart, and bone from chest X-rays. Its use has been shown to increase the accuracy of image reading by up to 25% when assisting doctors.
While specific technical details for DrAid for Radiology v1's data handling were not provided, as an FDA-approved medical AI product, it is expected to adhere to stringent data privacy and security regulations. This typically includes compliance with standards like HIPAA in the US, ensuring secure handling, storage, and transmission of patient medical imaging data.
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| Last Verified: 2026-04-19 | First Added: 2026-04-19