• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to secondary sidebar
  • Skip to footer

  • COVID-19
  • Opinion
  • Health IT
    • Behavioral Health
    • Care Coordination
    • EMR/EHR
    • Interoperability
    • Patient Engagement
    • Population Health Management
    • Revenue Cycle Management
    • Social Determinants of Health
  • Digital Health
    • Artificial Intelligence
    • Blockchain
    • Mobile Health
    • Precision Medicine
    • Telehealth
    • Wearables
  • Startups
  • M&A
  • Value-based Care
    • Accountable Care (ACOs)
    • Medicare Advantage
  • Life Sciences
  • Research

Eko and Mayo Clinic Collaborate on Machine Learning Algorithm to Help Physicians Fight Heart Disease

by Jasmine Pennic 10/25/2018 Leave a Comment

  • LinkedIn
  • Twitter
  • Facebook
  • Email
  • Print

Eko Core

Eko and Mayo Clinic collaborate on a machine learning-based algorithm to help physicians better screen for potentially dangerous heart diseases.

Eko, creators of a heart and lung monitoring platform that combines non-invasive cardiac sensors with machine learning, has announced a collaboration with Mayo Clinic to develop and commercialize a machine learning-based algorithm that screens patients for the presence of a low ejection fraction – a weak heart pump. The collaborative effort combines Mayo’s cardiovascular database containing millions of ECGs and healthcare screenings – with Eko’s smart stethoscope and machine-learning algorithm and software platform.

How It Works

This allows ANY doctor to seamlessly tap the knowledge of an experienced cardiologist to determine if a weak heart pump is present simply by putting a stethoscope on a person’s chest for a few seconds. With this algorithm, Eko can help screen patients in seconds in the doctor’s office. Because the Eko tool can be used by any healthcare provider, it may detect heart function abnormalities earlier and in patients who might not otherwise be screened for heart disease.

The technology leverages the Mayo Clinic’s vast cardiovascular database and their expertise in medical AI and heart disease screening and combines it with Eko’s cardiac monitoring platform. Traditionally, ejection fraction is measured by imaging techniques such as echocardiography, which is a powerful but expensive and time-consuming test that is less accessible to most people in the U.S. and around the world than a doctor with a stethoscope.  

“With this collaboration, we hope to transform the stethoscope in the pocket of every physician and nurse from a hand tool to a power tool,” said Paul Friedman, M.D., Chair of Cardiovascular Medicine at Mayo Clinic in Rochester, MN. “The community practitioner performing high school sports physicals and the surgeon about to operate may be able to seamlessly tap the
knowledge of an experienced cardiologist to determine if a weak heart pump is present simply by putting a stethoscope on a person’s chest for a few seconds.”  

Eko hopes to gain FDA clearance approval for the technology after running clinical studies with Mayo Clinic. 

  • LinkedIn
  • Twitter
  • Facebook
  • Email
  • Print

Tagged With: algorithms, Artificial Intelligence, Eko Devices, heart disease, Machine Learning

Get in-depth healthcare technology analysis and commentary delivered straight to your email weekly

Reader Interactions

Primary Sidebar

Subscribe to HIT Consultant

Latest insightful articles delivered straight to your inbox weekly.

Submit a Tip or Pitch

Knowledge Hub

10 Critical KPIs Every Successful Healthcare Organization is Implementing10 Critical KPIs Every Successful Healthcare Organization is Implementing

How to Build Hybrid Care Models Around Remote Patient Monitoring

How to Build Hybrid Care Models Around Remote Patient Monitoring

Most Popular

M&A: Florence Acquires Virtual Care Solution Zipnosis

M&A: Florence Acquires Virtual Care Solution Zipnosis

Adopting Value-Based Care Models for Autism Care Is Imperative

Why Adopting Value-Based Care Models for Autism Care Is Imperative

UNC Health to Pilot Epic, Microsoft’s Generative AI Tool

UNC Health to Pilot Epic, Microsoft’s Generative AI Tool

Vanderbilt University Medical Center Taps Philips Reduce Carbon Footprint

Vanderbilt University Medical Center Taps Philips to Reduce Carbon Footprint

Denials Management Named Most Time-Consuming Task in RCM

Denials Management Named Most Time-Consuming Task in RCM

How AI Can Eliminate Surprise Bills, Improve Payment Integrity

AI Can Eliminate Surprise Bills, Improve Payment Integrity

Q/A: IQVIA’s Global Lead Talks Unlocking AI for Drug Repurposing

M&A: Kaiser Acquires Geisinger, Forms Risant Health

5 Executives Weigh in on VBC Impact on Kaiser/Geisinger Deal

Digital Health Executive Hires & Departures

Digital Health Executive Hires & Departures: Ed Marx Departure, Particle Health CEO, Rhapsody CFO, Others

Catalyst by Wellstar Launches $100M Digital Health Venture Fund

Catalyst by Wellstar Launches $100M Digital Health Venture Fund

Secondary Sidebar

Footer

Company

  • About Us
  • Advertise with Us
  • Reprints and Permissions
  • 2023 Editorial Calendar
  • Submit An Op-Ed
  • Contact
  • Subscribe

Editorial Coverage

  • Opinion
  • Health IT
    • Care Coordination
    • EMR/EHR
    • Interoperability
    • Population Health Management
    • Revenue Cycle Management
  • Digital Health
    • Artificial Intelligence
    • Blockchain Tech
    • Precision Medicine
    • Telehealth
    • Wearables
  • Startups
  • Value-Based Care
    • Accountable Care
    • Medicare Advantage

Connect

Subscribe to HIT Consultant Media

Latest insightful articles delivered straight to your inbox weekly

Copyright © 2023. HIT Consultant Media. All Rights Reserved. Privacy Policy |