HealthCXR

by Zebra Medical Vision  · Based in Israel → — AI-Powered Chest X-ray Analysis for Rapid Triage
Emergency Medicine Pulmonology Radiology
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Regulatory Status Disclosed

Overview

HealthCXR by Zebra Medical Vision (now part of Nanox.AI) is an artificial intelligence-powered software workflow tool designed to aid the clinical assessment of adult Chest X-Ray cases. It automatically identifies suspected findings, specifically pleural effusion, on chest X-rays (CR, DR, and DX scans) and notifies the PACS/workstation of the presence of this critical finding. This notification allows for worklist prioritization and triage of identified scans, assisting clinicians in viewing prioritized scans more quickly. The tool is intended to support radiologists and healthcare providers in making faster and more accurate diagnoses, thereby improving patient care, particularly for acute pathologies. It is not intended to direct attention to specific portions or anomalies of an image, nor is it for stand-alone clinical decision-making, but rather to be used in conjunction with additional patient information and professional judgment.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automatic identification of suspected pleural effusion on chest X-rays
  • Notification to PACS/workstation for worklist prioritization
  • Triage of chest X-ray cases
  • Analyzes CR, DR, and DX scans
  • Aids clinical assessment (not for stand-alone diagnosis)
  • Seamless integration with existing PACS and EHR systems
  • AI-assisted triage and prioritization
  • Reduces diagnostic interpretation time
  • Enhances diagnostic accuracy

Use Cases

  • Prioritizing chest X-ray cases with suspected pleural effusion
  • Reducing turnaround time for radiologists
  • Improving patient care through faster diagnosis of acute pathology
  • Assisting clinicians in viewing prioritized scans
  • Optimizing radiology department workflows

What Physicians Need to Know

DICOM Support & Standards
HealthCXR is designed to operate with DICOM-compliant systems, automatically retrieving chest X-ray studies and sending notification results to PACS/workstations. DICOM is the international standard for transmitting, storing, and exchanging medical imaging information, ensuring interoperability.
PACS Integration Method
The tool integrates by making case-level output available to a PACS/workstation for worklist prioritization or triage. It sends notification results to the PACS/workstation or a standalone desktop application for prioritized review, operating in parallel with the standard care workflow.
AI Model Architecture (deep learning approach)
HealthCXR utilizes an artificial intelligence algorithm, specifically a deep learning approach, to analyze frontal chest X-ray images for suspected pleural effusion. Deep learning models, such as convolutional neural networks (CNNs), are commonly used for CXR interpretation.
Processing Speed (per study)
The mean processing time for HealthCXR was approximately 20 to 28 seconds per study.
FDA Clearance Pathway (510k/De Novo)
HealthCXR (Zebra Medical Vision, Ltd.) received FDA clearance via the 510(k) pathway. Its performance was validated and found to be substantially equivalent to a predicate device (HealthPNX, K190362).
Supported Modalities (CT/MRI/X-ray/US)
HealthCXR is specifically designed to analyze adult frontal Chest X-ray images.
Sensitivity & Specificity Data
Performance was validated on a retrospective cohort of 554 chest X-ray cases. HealthCXR demonstrated an AUC of 0.9885, with sensitivities of 96.74% and 93.84%, and specificities of 93.17% and 97.12% at two operating points for detecting pleural effusion.
Physician Tip

When utilizing HealthCXR, remember it functions as a workflow aid for prioritizing critical chest X-ray cases, particularly for suspected pleural effusion. It is not a diagnostic tool and should not be used for standalone clinical decision-making. Always perform a comprehensive review of the full imaging study and integrate AI findings with clinical context. Be aware of the reported sensitivity and specificity, and understand that performance can vary with different patient populations or image quality. Leverage the tool to manage caseload efficiently, but maintain your diagnostic oversight.

HealthCXR integrates with existing PACS/workstations by receiving DICOM studies and sending back notifications for worklist prioritization. Ensure your PACS is configured to properly receive and display these AI-generated alerts. For optimal workflow, consider how these alerts fit into your current reading protocols and if any adjustments are needed for seamless integration into your radiology information system (RIS) or electronic health record (EHR) for a unified patient record. Adherence to DICOM and HL7 standards is crucial for effective data exchange.

Details

Category Radiology & Imaging AI, Triage & ER/ICU AI
Pricing Contact for pricing
  • $1 USD per scan (historical AI1 initiative for all algorithms, as of 2017-2021); contact vendor for current pricing
DeploymentCloud / On-premise / Hybrid
Compliance
BAA AvailableUnknown AI-estimated
HIPAA Compliant Yes AI-estimated
FDA Status Yes AI-estimated

HealthCXR received FDA 510(k) clearance (K192320) on November 26, 2019, for the identification and triaging of pleural effusion in chest X-rays.
Integrations
EHR Not specified
Specialties Emergency Medicine, Pulmonology, Radiology

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Press & Coverage

The Jerusalem Post
Zebra wins FDA clearance for AI-based pleural effusion diagnosis tech
Zebra Medical Vision received FDA clearance for its HealthCXR device, an AI-powered solution for identifying and triaging pleural effusion in chest x-rays. The deep-learning solution quickly notifies radiologists of findings suggestive of pleural effusion, enabling them to prioritize urgent cases.
2019-11
AuntMinnie
Zebra gets FDA OK for pleural effusion AI software
Zebra Medical Vision's HealthCXR AI software has received FDA 510(k) clearance for the identification and triage of pleural effusion on chest x-rays. The software automatically detects signs of pleural effusion from various scan types and alerts radiologists for faster diagnosis.
2019-12
Medical Device Network
Zebra Medical Vision gets approval for HealthCXR imaging device
Israel's Zebra Medical Vision secured FDA 510(k) clearance for its AI-powered HealthCXR device, designed to identify and triage pleural effusion in chest X-rays. This device is an addition to Zebra's AI1 suite of triage and prioritization applications for chest X-rays.
2019-11
The Times of Israel
Zebra Medical gets FDA nod for device that detects water in lungs
Zebra Medical Vision received its fourth FDA clearance for HealthCXR, a device that uses AI to identify pleural effusion (water in the lungs) from medical scans. This technology helps radiologists prioritize cases and provide quicker treatment.
2019-11
NoCamels
Zebra Medical Vision Secures FDA Nod For Device That Identifies Water In The Lungs
Zebra Medical Vision announced its fourth FDA 510(k) clearance for the HealthCXR device, which is designed for the identification and triaging of pleural effusion in chest X-rays. This marks the first FDA nod specifically for pleural effusion.
2019-11
Applied Radiology
The Ubiquity of AI at RSNA 2019
At RSNA 2019, Zebra Medical Vision's HealthCXR, part of its AI1 bundle, received a new FDA clearance. The device can now identify and triage pleural effusions on chest X-rays, playing a significant role in triage according to Dr. J.J. Visser.
2020-01
AAP Publications
Machine Learning for Child and Adolescent Health: A Systematic Review
A systematic review on machine learning in child and adolescent health highlights HealthCXR's capability in detecting pleural effusion on chest radiographs with over 98% accuracy.
2021-01
BMJ Health & Care Informatics
How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices
An analysis of FDA-approved medical devices incorporating machine learning lists HealthCXR by Zebra Medical Vision, Ltd. as a device approved in 2019 for diagnostic and triage tasks.
2021-04

Videos

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Frequently Asked Questions

HealthCXR is designed to function as an intelligent assistant, integrating with existing PACS systems to automate repetitive tasks, prioritize urgent cases, and highlight potential abnormalities for radiologist review. This allows clinicians to focus their expertise on complex interpretations and clinical decision-making, enhancing efficiency and potentially reducing workload.
For clinical use in the US, HealthCXR would require appropriate regulatory clearance, such as FDA approval or 510(k) clearance, which indicates its safety and efficacy as a medical device. Regarding patient data privacy, HealthCXR must be HIPAA-compliant, meaning it employs robust technical and administrative safeguards like data encryption, access controls, and requires a Business Associate Agreement (BAA) with the vendor to protect Protected Health Information (PHI).
Like any AI, HealthCXR has limitations, including potential biases from its training data, reduced accuracy with atypical presentations, or poor image quality. Over-reliance on AI can lead to diagnostic complacency or 'AI hallucinations,' underscoring that it should augment, not replace, human clinical judgment.
HealthCXR aims to enhance diagnostic accuracy and efficiency by identifying subtle patterns and anomalies that human interpretation might miss, potentially reducing false positives and improving early detection. Studies suggest that human-AI collaboration often outperforms either alone, and AI can significantly reduce radiologists' workloads.
Pricing for healthcare AI solutions like HealthCXR often involves various models, including fixed costs, consumption-based (per-study or per-patient), or customized enterprise solutions. Hybrid models combining a base subscription fee with variable components or performance incentives are also common, with a strong preference for transparency and predictability in billing.
HealthCXR would have been trained on vast, high-quality datasets of anonymized chest X-ray images, often meticulously curated and annotated by expert radiologists to ensure accuracy. Its performance is rigorously validated on independent and diverse datasets to ensure generalizability and reliability across various patient populations and clinical settings.
HealthCXR could be designed as a general-purpose tool to identify a broad range of abnormalities on chest X-rays, or it might be specialized to detect specific conditions like pneumothorax, lung nodules, or tuberculosis. Its specific capabilities and intended use would be clearly defined by its regulatory clearance and product specifications.

Compare HealthCXR

VS
CINA-VCF vs HealthCXR
Radiology & Imaging AI Adjacent · 65/100
CINA-VCF focuses on detecting vertebral compression fractures on CT scans, particularly in adults aged 50 and over, while HealthCXR specializes in identifying pleural effusion on chest X-rays. Both…
VS
CINA-CSpine vs HealthCXR
Radiology & Imaging AI Adjacent · 70/100
CINA-CSpine is an AI triage tool specifically for detecting acute cervical spine fractures on neck CT scans, primarily benefiting neurosurgery and emergency medicine. In contrast, HealthCXR is an…
VS
SwiftMR vs HealthCXR
Radiology & Imaging AI Adjacent · 65/100
SwiftMR is designed to enhance MRI image quality and significantly reduce scan times across all MRI vendors and sequences. In contrast, HealthCXR specializes in the automatic identification and…
VS
QuickRad vs HealthCXR
Radiology & Imaging AI Adjacent · 65/100
QuickRad is a comprehensive AI-integrated PACS and RIS system designed for end-to-end radiology workflow management, including image handling, reporting, and analytics. In contrast, HealthCXR is a specialized AI…

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Suggest an Edit → | Last Verified: 2026-04-19 | First Added: 2026-04-19
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