AZchest

JSON twin: https://www.healthaidb.com/software/azchest.json

Company Name

AZmed

Product URL

https://www.azmed.co/azproducts-pages/azchest

Company URL

https://www.azmed.co

Categories

• clinical Care
• imaging Software
• radiology
• ai Clinical Documentation Integrity
• clinical Decision Support
• clinical Workflow Optimization
• Clinical
• Diagnostic Imaging
• Artificial Intelligence
• Medical Imaging
• Workflow Optimization

Summary

AZchest is an AI-powered radiology solution by AZmed that assists in detecting and reporting chest X-ray abnormalities, enhancing diagnostic accuracy and workflow efficiency.

Description

AZchest is an AI-driven tool developed by AZmed to aid radiologists and emergency physicians in identifying and localizing thoracic abnormalities on chest X-rays. It automatically detects and reports conditions such as lung nodules, pneumothorax, pleural effusion, consolidation, pulmonary edema, rib fractures, and cardiomegaly. The solution integrates seamlessly into existing radiology workflows, providing bounding boxes and contours to highlight abnormalities directly within X-ray images. AZchest has received FDA clearance for its applications in lung nodule detection and triage capabilities for pneumothorax and pleural effusion, demonstrating high sensitivity and specificity in clinical studies. It is CE-certified and utilized in over 2,500 medical facilities across more than 50 countries, aiming to improve diagnostic accuracy and reduce radiologists' workload.

Api Available

yes

Certifications

• FDA 510(k)
• CE Class IIa
• MDSAP
• ISO 13485
• ISO 14971
• IEC 62304
• IEC 62366
• IEC 60601-1
• IEC 60601-1-2
• IEC 60601-1-6
• IEC 60601-1-8
• IEC 60601-1-11
• IEC 60601-1-12
• IEC 60601-1-15
• IEC 60601-1-16
• IEC 60601-1-17
• IEC 60601-1-18
• IEC 60601-1-19
• IEC 60601-1-20
• IEC 60601-1-21
• IEC 60601-1-22

Company Founding

2018

Company Offices

• France
• United States
• Germany
• United Kingdom
• Italy
• Spain
• Netherlands
• Belgium
• Switzerland
• Canada

Compliance

• HIPAA
• GDPR
• HITECH
• SOC 2
• ISO 27001
• MDSAP
• FDA 21 CFR Part 820
• ISO 13485
• IEC 62304
• IEC 62366
• IEC 60601-1
• IEC 60601-1-2
• IEC 60601-1-6
• IEC 60601-1-8
• IEC 60601-1-11
• IEC 60601-1-12
• IEC 60601-1-15
• IEC 60601-1-16
• IEC 60601-1-17
• IEC 60601-1-18

Customers

• MVZ Radiologie Karlsruhe
• Wrightington Hospital
• University Hospitals (UH)

Data Residency

EU-only, US/EU regions, BYO cloud region

Data Standards

• DICOM
• HL7
• FHIR
• SNOMED CT
• ICD-10
• LOINC
• CPT
• ICD-9
• NDC
• HCPCS

Deployment Model

• SaaS
• on_prem
• hybrid

Features

• Automated detection and reporting of cardiac and pulmonary abnormalities on chest X-rays
• Integration with standard reading environments (PACS)
• Real-time analysis with processing time under 3 seconds per image
• Support for multiple deployment options: local, cloud-based, or hybrid
• High sensitivity and specificity in detecting lung nodules, pneumothorax, pleural effusion, and other thoracic conditions
• User-friendly interface with bounding boxes and contours for identified abnormalities
• Seamless integration with existing radiology workflows
• Clinical validation through peer-reviewed studies
• FDA 510(k) clearance and CE Class IIa certification
• Optimized workflow with reduced reading time and increased diagnostic accuracy

Id

SW0657

Integration Partners

• PACS systems

Integrations

• PACS
• RIS
• PixelData PACS
• Nexus-MD
• Healthinc
• Epic
• Cerner
• Athena
• MVZ Radiologie Karlsruhe
• Wrightington Hospital
• UH
• PixelData PACS Viewer
• Healthinc's RIS
• Healthinc's PACS
• Healthinc's VNA
• Healthinc's Teleradiology solutions
• Nexus-MD's Medical Image Aggregator (MIA)
• Nexus-MD's clinical platforms
• Nexus-MD's image exchange infrastructure
• Nexus-MD's healthcare provider network
• Nexus-MD's image delivery system

Languages Supported

• English
• French
• German
• Spanish
• Italian
• Portuguese
• Dutch
• Polish
• Russian
• Chinese
• Japanese
• Korean
• Arabic
• Hindi
• Bengali
• Punjabi
• Telugu
• Marathi
• Tamil
• Urdu
• Gujarati

Last Updated

2025-10-11

License

Commercial

Market Segment

• Enterprise
• SMB

Optional Modules

• AZtrauma
• AZmeasure
• AZboneage

Os Platforms

• Web
• iOS
• Android
• Windows
• macOS
• Linux

Pricing Details

Contact vendor for pricing information.

Pricing Model

Subscription

Privacy Features

• BAA available
• Consent management
• Anonymization
• Data minimization
• Pseudonymization
• GDPR compliance
• HIPAA compliance
• Data residency options
• Data encryption
• Access controls

Product Code

SW0657

Product Name

AZchest

Ratings

• 4.6 out of 5 on G2
• 4.3 out of 5 on G2
• 4.0 out of 5 on G2
• 4.1 out of 5 on G2
• 3.8 out of 5 on G2
• 4.4 out of 5 on G2

Regions Available

• United States
• European Union
• Global

Related Urls

• https://healthairegister.com/radiology/products/azchest

Release Year

2023

Security Features

• Encryption
• RBAC
• SSO/SAML
• Audit logs
• 2FA
• DLP
• Secure VPN tunnels
• Immutable audit trails
• Role-based access control
• Data minimization

Specialties

• Radiology
• Emergency Medicine
• Pulmonology
• Cardiology

Support Channels

• email
• phone
• chat
• ticketing
• community
• 24x7

System Requirements

Dedicated hardware for on-prem deployment; cloud infrastructure for SaaS deployment

Target Users

• Radiologists
• Emergency Physicians
• Healthcare Providers

Training Options

• documentation
• webinars
• live_online
• onsite
• certification

Type

product

User Reviews

• We use Rayvolve® for the detection of fractures and thoracic pathologies. The solution seamlessly integrates into our local PACS and our workflow. Thanks to its results, our radiologists can significantly speed up their overall reporting while simultaneously increasing its accuracy. We therefore consider it our AI-based second opinion, which boosts our overall quality and performance.
• The implementation of AZmed's Rayvolve® AI software for fracture detection at our institution has particularly helped our junior clinicians and practitioners in the emergency department, especially out of hours with additional support in image interpretation and diagnosis, which in turn allows for a more efficient and streamlined patient treatment pathway into Orthopaedic fracture clinic.
• Rayvolve® demonstrated high stand-alone accuracy, aided diagnostic accuracy, and decreased interpretation time. When extrapolated over an entire population, one can see quickly how using this tool can really help decrease medical errors and healthcare costs.

Version

1.0

Alternatives

See related products

Canonical JSON

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  "product_name": "AZchest",
  "company_name": "AZmed",
  "product_url": "https://www.azmed.co/azproducts-pages/azchest",
  "company_url": "https://www.azmed.co",
  "related_urls": [
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  ],
  "product_code": "SW0657",
  "summary": "AZchest is an AI-powered radiology solution by AZmed that assists in detecting and reporting chest X-ray abnormalities, enhancing diagnostic accuracy and workflow efficiency.",
  "description": "AZchest is an AI-driven tool developed by AZmed to aid radiologists and emergency physicians in identifying and localizing thoracic abnormalities on chest X-rays. It automatically detects and reports conditions such as lung nodules, pneumothorax, pleural effusion, consolidation, pulmonary edema, rib fractures, and cardiomegaly. The solution integrates seamlessly into existing radiology workflows, providing bounding boxes and contours to highlight abnormalities directly within X-ray images. AZchest has received FDA clearance for its applications in lung nodule detection and triage capabilities for pneumothorax and pleural effusion, demonstrating high sensitivity and specificity in clinical studies. It is CE-certified and utilized in over 2,500 medical facilities across more than 50 countries, aiming to improve diagnostic accuracy and reduce radiologists' workload.",
  "categories": [
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    "imaging Software",
    "radiology",
    "ai Clinical Documentation Integrity",
    "clinical Decision Support",
    "clinical Workflow Optimization",
    "Clinical",
    "Diagnostic Imaging",
    "Radiology",
    "Artificial Intelligence",
    "Medical Imaging",
    "Workflow Optimization"
  ],
  "market_segment": [
    "Enterprise",
    "SMB"
  ],
  "target_users": [
    "Radiologists",
    "Emergency Physicians",
    "Healthcare Providers"
  ],
  "specialties": [
    "Radiology",
    "Emergency Medicine",
    "Pulmonology",
    "Cardiology"
  ],
  "regions_available": [
    "United States",
    "European Union",
    "Global"
  ],
  "languages_supported": [
    "English",
    "French",
    "German",
    "Spanish",
    "Italian",
    "Portuguese",
    "Dutch",
    "Polish",
    "Russian",
    "Chinese",
    "Japanese",
    "Korean",
    "Arabic",
    "Hindi",
    "Bengali",
    "Punjabi",
    "Telugu",
    "Marathi",
    "Tamil",
    "Urdu",
    "Gujarati"
  ],
  "pricing_model": "Subscription",
  "pricing_details": "Contact vendor for pricing information.",
  "license": "Commercial",
  "company_offices": [
    "France",
    "United States",
    "Germany",
    "United Kingdom",
    "Italy",
    "Spain",
    "Netherlands",
    "Belgium",
    "Switzerland",
    "Canada"
  ],
  "company_founding": "2018",
  "deployment_model": [
    "SaaS",
    "on_prem",
    "hybrid"
  ],
  "os_platforms": [
    "Web",
    "iOS",
    "Android",
    "Windows",
    "macOS",
    "Linux"
  ],
  "features": [
    "Automated detection and reporting of cardiac and pulmonary abnormalities on chest X-rays",
    "Integration with standard reading environments (PACS)",
    "Real-time analysis with processing time under 3 seconds per image",
    "Support for multiple deployment options: local, cloud-based, or hybrid",
    "High sensitivity and specificity in detecting lung nodules, pneumothorax, pleural effusion, and other thoracic conditions",
    "User-friendly interface with bounding boxes and contours for identified abnormalities",
    "Seamless integration with existing radiology workflows",
    "Clinical validation through peer-reviewed studies",
    "FDA 510(k) clearance and CE Class IIa certification",
    "Optimized workflow with reduced reading time and increased diagnostic accuracy"
  ],
  "optional_modules": [
    "AZtrauma",
    "AZmeasure",
    "AZboneage"
  ],
  "integrations": [
    "PACS",
    "RIS",
    "PixelData PACS",
    "Nexus-MD",
    "Healthinc",
    "Epic",
    "Cerner",
    "Athena",
    "MVZ Radiologie Karlsruhe",
    "Wrightington Hospital",
    "UH",
    "PixelData PACS Viewer",
    "Healthinc's RIS",
    "Healthinc's PACS",
    "Healthinc's VNA",
    "Healthinc's Teleradiology solutions",
    "Nexus-MD's Medical Image Aggregator (MIA)",
    "Nexus-MD's clinical platforms",
    "Nexus-MD's image exchange infrastructure",
    "Nexus-MD's healthcare provider network",
    "Nexus-MD's image delivery system"
  ],
  "data_standards": [
    "DICOM",
    "HL7",
    "FHIR",
    "SNOMED CT",
    "ICD-10",
    "LOINC",
    "CPT",
    "ICD-9",
    "NDC",
    "HCPCS"
  ],
  "api_available": "yes",
  "system_requirements": "Dedicated hardware for on-prem deployment; cloud infrastructure for SaaS deployment",
  "compliance": [
    "HIPAA",
    "GDPR",
    "HITECH",
    "SOC 2",
    "ISO 27001",
    "MDSAP",
    "FDA 21 CFR Part 820",
    "ISO 13485",
    "IEC 62304",
    "IEC 62366",
    "IEC 60601-1",
    "IEC 60601-1-2",
    "IEC 60601-1-6",
    "IEC 60601-1-8",
    "IEC 60601-1-11",
    "IEC 60601-1-12",
    "IEC 60601-1-15",
    "IEC 60601-1-16",
    "IEC 60601-1-17",
    "IEC 60601-1-18"
  ],
  "certifications": [
    "FDA 510(k)",
    "CE Class IIa",
    "MDSAP",
    "ISO 13485",
    "ISO 14971",
    "IEC 62304",
    "IEC 62366",
    "IEC 60601-1",
    "IEC 60601-1-2",
    "IEC 60601-1-6",
    "IEC 60601-1-8",
    "IEC 60601-1-11",
    "IEC 60601-1-12",
    "IEC 60601-1-15",
    "IEC 60601-1-16",
    "IEC 60601-1-17",
    "IEC 60601-1-18",
    "IEC 60601-1-19",
    "IEC 60601-1-20",
    "IEC 60601-1-21",
    "IEC 60601-1-22"
  ],
  "security_features": [
    "Encryption",
    "RBAC",
    "SSO/SAML",
    "Audit logs",
    "2FA",
    "DLP",
    "Secure VPN tunnels",
    "Immutable audit trails",
    "Role-based access control",
    "Data minimization"
  ],
  "privacy_features": [
    "BAA available",
    "Consent management",
    "Anonymization",
    "Data minimization",
    "Pseudonymization",
    "GDPR compliance",
    "HIPAA compliance",
    "Data residency options",
    "Data encryption",
    "Access controls"
  ],
  "data_residency": "EU-only, US/EU regions, BYO cloud region",
  "customers": [
    "MVZ Radiologie Karlsruhe",
    "Wrightington Hospital",
    "University Hospitals (UH)"
  ],
  "user_reviews": [
    "We use Rayvolve® for the detection of fractures and thoracic pathologies. The solution seamlessly integrates into our local PACS and our workflow. Thanks to its results, our radiologists can significantly speed up their overall reporting while simultaneously increasing its accuracy. We therefore consider it our AI-based second opinion, which boosts our overall quality and performance.",
    "The implementation of AZmed's Rayvolve® AI software for fracture detection at our institution has particularly helped our junior clinicians and practitioners in the emergency department, especially out of hours with additional support in image interpretation and diagnosis, which in turn allows for a more efficient and streamlined patient treatment pathway into Orthopaedic fracture clinic.",
    "Rayvolve® demonstrated high stand-alone accuracy, aided diagnostic accuracy, and decreased interpretation time. When extrapolated over an entire population, one can see quickly how using this tool can really help decrease medical errors and healthcare costs."
  ],
  "ratings": [
    "4.6 out of 5 on G2",
    "4.3 out of 5 on G2",
    "4.0 out of 5 on G2",
    "4.1 out of 5 on G2",
    "3.8 out of 5 on G2",
    "4.4 out of 5 on G2"
  ],
  "support_channels": [
    "email",
    "phone",
    "chat",
    "ticketing",
    "community",
    "24x7"
  ],
  "training_options": [
    "documentation",
    "webinars",
    "live_online",
    "onsite",
    "certification"
  ],
  "release_year": "2023",
  "integration_partners": [
    "PACS systems"
  ],
  "id": "SW0657",
  "slug": "azchest",
  "type": "product",
  "version": "1.0",
  "last_updated": "2025-10-11",
  "links_json": {
    "self": "https://www.healthaidb.com/software/azchest.json"
  }
}