What You Should Know:
- Boehringer Ingelheim, a global leader in animal health, and Eko Health, a pioneer in applying artificial intelligence (AI) for early disease detection, have announced a strategic collaboration. The partnership aims to enhance the early detection and diagnosis of heart disease in dogs by combining Boehringer's expertise in canine cardiology with Eko Health's powerful AI algorithms and digital stethoscopes.
- The collaboration will leverage Eko Health's
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heart arrhythmia detection
AliveCor Unveils KardiaMobile 6L Max & KardiaAlert for Advanced Personal ECG Monitoring
What You Should Know:
- AliveCor, a leader in FDA-cleared personal electrocardiogram (ECG) technology, today announced the launch of its most advanced personal ECG system, the AI-powered KardiaMobile® 6L Max.
- Accompanying this device is KardiaAlert™, a first-of-its-kind feature available exclusively to subscribers of AliveCor's KardiaCare service. Together, these innovations aim to provide users with more comprehensive detections and insights, monitor heart rhythms for
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AISAP’s AI-Powered Cardiac Ultrasound Receives FDA Clearance
What You Should Know:
- AISAP, a medical technology company specializing in AI-powered point-of-care assisted diagnosis (POCAD) solutions, announced today that it has received FDA 510(k) clearance for its groundbreaking CARDIO software platform.
- AISAP CARDIO is a cloud-based software package that combines four computer-assisted diagnosis (CADx) modules for valvular pathologies and eight key measurements into a single, user-friendly platform.
Point-of-Care
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WearLinq Acquires AMI Cardiac Monitoring, Raises $6.7M for FDA-Cleared 6-Lead ECG Device
What You Should Know:
- WearLinq, a leader in wearable health monitoring, announced a strategic acquisition of AMI Cardiac Monitoring, LLC, a seasoned player in ambulatory cardiac monitoring.
- The acquisition, coupled with a recent $6.7M funding round, positions WearLinq to significantly expand access to their innovative eWave 6-lead ECG monitor and revolutionize the fight against atrial fibrillation (AFib), which recently received FDA 510(k) clearance.
Tackling the
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New AI ECG Algorithm Beats Standard Approaches for Detecting Heart Attacks
What You Should Know:
A new machine learning model uses electrocardiogram (ECG) readings to diagnose and classify heart attacks faster and more accurately than current approaches, according to a study led by University of Pittsburgh researchers that published today in Nature Medicine.The model was developed by co-author Ervin Sejdić, Ph.D., associate professor at The Edward S. Rogers Department of Electrical and Computer Engineering at the University of Toronto and the Research
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AliveCor Launches KardiaMobile Card, World’s First Credit-Card-Sized Personal ECG
What You Should Know:
- Today, AliveCor is launching KardiaMobile Card, the latest generation of personal electrocardiogram (ECG) technology that, at the size of the credit card, is the thinnest, lightest ECG device ever created and fits in any wallet.
- The FDA-cleared KardiaMobile Card detects six of the most common heart arrhythmias in 30 seconds – something no other personal ECG can do – making it the most important card in your wallet.
KardiaMobile Card: Instant Feedback on Heart
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Google Awards $1M to U. Of Sydney to Develop AI Solution to Prevent Heart Attacks
The University of
Sydney’s Westmead Applied
Research Centre has been awarded
$1M as part of Australia’s inaugural Google.org AI Impact Challenge prize to
develop a customized digital health solution
powered by artificial
intelligence (AI) to reduce the risk of heart attacks. The prize was
presented to Westmead Applied Research Centre (WARC) led by Professor Clara Chow, a cardiologist at
Westmead Hospital and the University of Sydney’s Westmead Clinical School as
well as academic
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Stanford Researchers Develop Algorithm to Diagnose Heart Arrhythmias
Stanford researchers from the Machine Learning Group have developed an algorithm that is able to outperform cardiologists in arrhythmia detection, according to research published on arXiv. The new deep learning algorithm can diagnose 14 types of heart rhythm defects, called arrhythmias and has the ability to sort through data from rural locations where people do not have routine access to cardiologists. Traditionally, patients suspected to have an arrhythmia will often get an electrocardiogram
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