New machine learning model predicts cardiac arrest in ICU patients using ECG data with high accuracy
In a recent article published in Npj Digital Medicine, researchers utilized electrocardiogram (ECG) data from a large retrospective cohort to extract various heart rate variability (HRV) measures.
Schematic representation of the ECG-LM model, a multi-modal large language model for cardiovascular diagnostics. The model integrates ECG data with patient information, offering accurate and ...
Researchers based in Australia and India recently published a study with their findings on developing improved electrodes for wearable heart monitors. The scientists researched options for developing ...
At HRS 2026, Dr. Song Zuo presented evidence that AI can detect atrial fibrillation with over 90% sensitivity, ...
Add Yahoo as a preferred source to see more of our stories on Google. Starting in February, Kern County will be the first county in California to deploy new AI-powered electrocardiogram machines to ...
At the 2026 Heart Rhythm Society meeting, researchers unveiled an AI system capable of detecting atrial fibrillation (AF) with over 90% accuracy using ECG analysis. The breakthrough could enable ...
An electrocardiogram (ECG) is a common physiological monitoring device used in medicine. However, conventional ECGs must be operated by medical professionals and are monotonous and time-consuming to ...
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