CogNet AI-MT

JSON twin: https://www.healthaidb.com/software/cognet-ai-mt.json

Company Name

MedCognetics

Product URL

https://www.medcognetics.com/cognet-ai

Company URL

https://www.medcognetics.com

Categories

• clinical Care
• diagnostic Support
• clinical Workflow Optimization
• Clinical
• Diagnostic
• Workflow Optimization

Summary

CogNet AI-MT is an AI-driven platform developed by MedCognetics to assist radiologists in analyzing mammograms, flagging suspicious findings to optimize workflow and enhance diagnostic accuracy.

Description

CogNet AI-MT utilizes artificial intelligence to analyze screening mammograms, flagging exams suggestive of suspicious findings. Developed through global collaboration, it is trained on diverse datasets to support real-world medical imaging variations. The platform can be deployed on-premises, in the cloud, or via the web, and is FDA 510(k) cleared for triage of mammogram images. It offers features like suspicious lesion indication, study prioritization, filtering, and integrated workflow, aiming to improve efficiency and accuracy in breast cancer detection.

Api Available

unknown

Certifications

• FDA 510(k)
• CE/MDR
• ONC
• ISO 13485

Company Founding

2020

Company Offices

• United States

Compliance

• HIPAA
• GDPR
• SOC 2
• ISO 27001

Customers

Data Residency

US/EU regions

Data Standards

• FHIR
• HL7 v2
• DICOM
• SNOMED
• ICD-10

Deployment Model

• SaaS
• on_prem
• hybrid

Features

• AI-driven analysis of screening mammograms
• Flagging of suspicious findings for worklist prioritization
• Collaboration with global clinical leaders
• Training on diverse patient datasets from multiple regions

Id

SW0404

Integration Partners

Integrations

• Blackford Platform

Languages Supported

• English

Last Updated

2025-10-11

License

commercial

Market Segment

• enterprise
• smb

Optional Modules

Os Platforms

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

Pricing Details

contact vendor

Pricing Model

subscription

Privacy Features

• BAA available
• consent mgmt
• anonymization
• data minimization

Product Code

SW0404

Product Name

CogNet AI-MT

Ratings

Regions Available

• United States
• United Kingdom
• Europe
• Middle East
• Asia
• South America
• Africa

Related Urls

• https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices

Release Year

Security Features

• Encryption
• RBAC
• SSO/SAML
• audit logs
• 2FA
• DLP

Specialties

• Radiology
• Mammography

Support Channels

System Requirements

GPU-powered EC2 instances, scalable model training environments using SageMaker, ECS, or EKS

Target Users

• radiologists
• imaging centers
• clinicians

Training Options

Type

product

User Reviews

Version

1.0

Alternatives

See related products

Canonical JSON

{
  "product_name": "CogNet AI-MT",
  "company_name": "MedCognetics",
  "product_url": "https://www.medcognetics.com/cognet-ai",
  "company_url": "https://www.medcognetics.com",
  "related_urls": [
    "https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices"
  ],
  "product_code": "SW0404",
  "summary": "CogNet AI-MT is an AI-driven platform developed by MedCognetics to assist radiologists in analyzing mammograms, flagging suspicious findings to optimize workflow and enhance diagnostic accuracy.",
  "description": "CogNet AI-MT utilizes artificial intelligence to analyze screening mammograms, flagging exams suggestive of suspicious findings. Developed through global collaboration, it is trained on diverse datasets to support real-world medical imaging variations. The platform can be deployed on-premises, in the cloud, or via the web, and is FDA 510(k) cleared for triage of mammogram images. It offers features like suspicious lesion indication, study prioritization, filtering, and integrated workflow, aiming to improve efficiency and accuracy in breast cancer detection.",
  "categories": [
    "clinical Care",
    "diagnostic Support",
    "clinical Workflow Optimization",
    "Clinical",
    "Diagnostic",
    "Workflow Optimization"
  ],
  "market_segment": [
    "enterprise",
    "smb"
  ],
  "target_users": [
    "radiologists",
    "imaging centers",
    "clinicians"
  ],
  "specialties": [
    "Radiology",
    "Mammography"
  ],
  "regions_available": [
    "United States",
    "United Kingdom",
    "Europe",
    "Middle East",
    "Asia",
    "South America",
    "Africa"
  ],
  "languages_supported": [
    "English"
  ],
  "pricing_model": "subscription",
  "pricing_details": "contact vendor",
  "license": "commercial",
  "company_offices": [
    "United States"
  ],
  "company_founding": "2020",
  "deployment_model": [
    "SaaS",
    "on_prem",
    "hybrid"
  ],
  "os_platforms": [
    "Web",
    "iOS",
    "Android",
    "Windows",
    "macOS",
    "Linux"
  ],
  "features": [
    "AI-driven analysis of screening mammograms",
    "Flagging of suspicious findings for worklist prioritization",
    "Collaboration with global clinical leaders",
    "Training on diverse patient datasets from multiple regions"
  ],
  "optional_modules": [],
  "integrations": [
    "Blackford Platform"
  ],
  "data_standards": [
    "FHIR",
    "HL7 v2",
    "DICOM",
    "SNOMED",
    "ICD-10"
  ],
  "api_available": "unknown",
  "system_requirements": "GPU-powered EC2 instances, scalable model training environments using SageMaker, ECS, or EKS",
  "compliance": [
    "HIPAA",
    "GDPR",
    "SOC 2",
    "ISO 27001"
  ],
  "certifications": [
    "FDA 510(k)",
    "CE/MDR",
    "ONC",
    "ISO 13485"
  ],
  "security_features": [
    "Encryption",
    "RBAC",
    "SSO/SAML",
    "audit logs",
    "2FA",
    "DLP"
  ],
  "privacy_features": [
    "BAA available",
    "consent mgmt",
    "anonymization",
    "data minimization"
  ],
  "data_residency": "US/EU regions",
  "customers": [],
  "user_reviews": [],
  "ratings": [],
  "support_channels": [],
  "training_options": [],
  "release_year": "",
  "integration_partners": [],
  "id": "SW0404",
  "slug": "cognet-ai-mt",
  "type": "product",
  "version": "1.0",
  "last_updated": "2025-10-11",
  "links_json": {
    "self": "https://www.healthaidb.com/software/cognet-ai-mt.json"
  }
}