ECG-AI LEF

JSON twin: https://www.healthaidb.com/software/ecg-ai-lef.json

Company Name

Anumana

Product URL

https://anumana.ai/ecg-ai-lef

Company URL

https://anumana.ai

Categories

• clinical Care
• diagnostic Support
• patient Facing
• Clinical
• Diagnostic

Summary

ECG-AI LEF is an FDA-cleared AI algorithm developed by Anumana to detect low ejection fraction (LEF) from standard 12-lead ECGs, aiding early heart failure diagnosis.

Description

ECG-AI LEF is an AI-powered software-as-a-medical device (SaMD) that analyzes routine 12-lead ECG data to identify low ejection fraction (EF), a key indicator of heart failure. Developed in collaboration with Mayo Clinic, it was FDA-cleared in September 2023 and has been validated in over 25 studies involving more than 40,000 patients. The algorithm integrates seamlessly into existing clinical workflows and has been recognized with the 2024 MedTech Breakthrough Award for Best New Technology Solution in Cardiology. It is currently available in the U.S. and under review in Europe. Additionally, it has been included in the Centers for Medicare & Medicaid Services (CMS) 2025 Hospital Outpatient Prospective Payment System final rule, facilitating reimbursement for its use in outpatient settings. Anumana has also partnered with Philips to integrate ECG-AI LEF into Philips' ECG portfolio, enhancing early cardiac diagnosis. Furthermore, a collaboration with AliveCor aims to advance ECG-AI algorithms for early detection of cardiac diseases on Kardia devices. The company was founded in 2020 and has offices in the United States and Europe.

Api Available

unknown

Certifications

• FDA 510(k) clearance
• FDA Breakthrough Device designation
• Category III CPT codes (+0764T, 0765T) effective Jan 1, 2023

Company Founding

2020

Company Offices

• United States
• Europe

Compliance

• FDA 510(k) clearance
• FDA Breakthrough Device designation
• HIPAA-compliant infrastructure
• PHI-secure infrastructure

Customers

Data Residency

United States

Data Standards

• ECG
• EHR
• HL7
• DICOM

Deployment Model

• SaaS
• cloud

Features

• AI detection of low left ventricular ejection fraction (LEF) from 12-lead ECG
• Web-based zero-footprint ECG Viewer
• Prior ECG history timeline with real-time AI results
• Clinical risk screening workflow integration
• Clinically validated model (multi-site studies, EAGLE trial)
• Supports point-of-care screening in primary, outpatient, and ED settings

Id

SW0893

Integration Partners

Integrations

• Philips IntelliSpace ECG
• Philips cardiographs
• AliveCor Kardia 12L ECG System
• InfoBionic.Ai MoMe ARC platform

Languages Supported

• English

Last Updated

2025-10-11

License

commercial

Market Segment

• enterprise
• smb

Optional Modules

Os Platforms

• Web

Pricing Details

contact vendor

Pricing Model

subscription

Privacy Features

• BAA available
• Consent management
• Anonymization
• Data minimization

Product Code

SW0893

Product Name

ECG-AI LEF

Ratings

Regions Available

• United States
• Europe

Related Urls

• https://elion.health/products/anumana

Release Year

Security Features

• Secure web-based viewer
• PHI protection
• Vulnerability disclosure program

Specialties

• Cardiology

Support Channels

System Requirements

Target Users

• clinicians
• patients

Training Options

Type

product

User Reviews

Version

1.0

Alternatives

See related products

Canonical JSON

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  "product_name": "ECG-AI LEF",
  "company_name": "Anumana",
  "product_url": "https://anumana.ai/ecg-ai-lef",
  "company_url": "https://anumana.ai",
  "related_urls": [
    "https://elion.health/products/anumana"
  ],
  "product_code": "SW0893",
  "summary": "ECG-AI LEF is an FDA-cleared AI algorithm developed by Anumana to detect low ejection fraction (LEF) from standard 12-lead ECGs, aiding early heart failure diagnosis.",
  "description": "ECG-AI LEF is an AI-powered software-as-a-medical device (SaMD) that analyzes routine 12-lead ECG data to identify low ejection fraction (EF), a key indicator of heart failure. Developed in collaboration with Mayo Clinic, it was FDA-cleared in September 2023 and has been validated in over 25 studies involving more than 40,000 patients. The algorithm integrates seamlessly into existing clinical workflows and has been recognized with the 2024 MedTech Breakthrough Award for Best New Technology Solution in Cardiology. It is currently available in the U.S. and under review in Europe. Additionally, it has been included in the Centers for Medicare & Medicaid Services (CMS) 2025 Hospital Outpatient Prospective Payment System final rule, facilitating reimbursement for its use in outpatient settings. Anumana has also partnered with Philips to integrate ECG-AI LEF into Philips' ECG portfolio, enhancing early cardiac diagnosis. Furthermore, a collaboration with AliveCor aims to advance ECG-AI algorithms for early detection of cardiac diseases on Kardia devices. The company was founded in 2020 and has offices in the United States and Europe.",
  "categories": [
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    "diagnostic Support",
    "patient Facing",
    "Clinical",
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  "market_segment": [
    "enterprise",
    "smb"
  ],
  "target_users": [
    "clinicians",
    "patients"
  ],
  "specialties": [
    "Cardiology"
  ],
  "regions_available": [
    "United States",
    "Europe"
  ],
  "languages_supported": [
    "English"
  ],
  "pricing_model": "subscription",
  "pricing_details": "contact vendor",
  "license": "commercial",
  "company_offices": [
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  "company_founding": "2020",
  "deployment_model": [
    "SaaS",
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  "os_platforms": [
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  "features": [
    "AI detection of low left ventricular ejection fraction (LEF) from 12-lead ECG",
    "Web-based zero-footprint ECG Viewer",
    "Prior ECG history timeline with real-time AI results",
    "Clinical risk screening workflow integration",
    "Clinically validated model (multi-site studies, EAGLE trial)",
    "Supports point-of-care screening in primary, outpatient, and ED settings"
  ],
  "optional_modules": [],
  "integrations": [
    "Philips IntelliSpace ECG",
    "Philips cardiographs",
    "AliveCor Kardia 12L ECG System",
    "InfoBionic.Ai MoMe ARC platform"
  ],
  "data_standards": [
    "ECG",
    "EHR",
    "HL7",
    "DICOM"
  ],
  "api_available": "unknown",
  "system_requirements": "",
  "compliance": [
    "FDA 510(k) clearance",
    "FDA Breakthrough Device designation",
    "HIPAA-compliant infrastructure",
    "PHI-secure infrastructure"
  ],
  "certifications": [
    "FDA 510(k) clearance",
    "FDA Breakthrough Device designation",
    "Category III CPT codes (+0764T, 0765T) effective Jan 1, 2023"
  ],
  "security_features": [
    "Secure web-based viewer",
    "PHI protection",
    "Vulnerability disclosure program"
  ],
  "privacy_features": [
    "BAA available",
    "Consent management",
    "Anonymization",
    "Data minimization"
  ],
  "data_residency": "United States",
  "customers": [],
  "user_reviews": [],
  "ratings": [],
  "support_channels": [],
  "training_options": [],
  "release_year": "",
  "integration_partners": [],
  "id": "SW0893",
  "slug": "ecg-ai-lef",
  "type": "product",
  "version": "1.0",
  "last_updated": "2025-10-11",
  "links_json": {
    "self": "https://www.healthaidb.com/software/ecg-ai-lef.json"
  }
}