Electrocardiogram (ECG) signal compression techniques have advanced considerably, driven by the increasing demands of telemedicine and remote patient monitoring. These methods are designed to reduce ...

Electrocardiogram (ECG) signal compression techniques are essential for the efficient storage, transmission and real‐time processing of cardiac data. Advanced methods utilising discrete wavelet ...

CAMBRIDGE, Mass.--(BUSINESS WIRE)--Anumana, Inc., a leading AI-driven health technology and nference portfolio company working in collaboration with Mayo Clinic, today announced U.S. Food and Drug ...

CAMBRIDGE, Mass.--(BUSINESS WIRE)--Anumana, a leading AI-driven health technology company and portfolio company of nference, announced a new study that revealed promising results in support of further ...

Paris-based Cardiologs has raised $6.5 million to support its AI-powered algorithm for ECG analysis. The round was led by a syndicate of investors including Idinvest, ISAI, Kurma Partners, and Partech ...

A new machine-learning tool can identify diabetes and prediabetes using ECG data, according to research recently published online in BMJ Innovations. “The motivation for the study was to search for ...

An artificial intelligence (AI) algorithm paired with the single-lead electrocardiogram (ECG) sensors on a smartwatch accurately diagnosed structural heart diseases, such as weakened pumping ability, ...

Please provide your email address to receive an email when new articles are posted on . Algorithms to improve ECG interpretability received FDA clearance. The solution is designed to reduce noise ...

An artificial intelligence algorithm for ECG interpretation (AI-ECG) is superior to conventional, guideline-recommended STEMI criteria for identifying patients with chest pain who have an occluded ...

People store large quantities of data in their electronic devices and transfer some of this data to others, whether for professional or personal reasons. Data compression methods are thus of the ...

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been developed. This ...