Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...
Overview Machine learning offers efficiency at scale, but trust depends on understanding how decisions are madeAs machine ...
SANTA CLARA, Calif.--(BUSINESS WIRE)--HeartBeam, Inc. (NASDAQ: BEAT), a medical technology company focused on transforming cardiac care through the power of personalized insights, today announced new ...
For the past decade, Eko Health has been advancing the use of artificial intelligence to help providers detect the early signs of disease, particularly heart and lung conditions, during routine ...
Researchers from New York City-based Mount Sinai have developed an AI algorithm to help physicians identify patients with hypertrophic cardiomyopathy by assigning a numeric probability risk assessment ...
HeartBeam’s Deep Learning Algorithms Demonstrate High Rates of Accuracy for Detecting Arrhythmias New study presented at HRX Live 2025 demonstrates continued advancement of company’s AI program ...
New research can transform how hospitals triage, risk-stratify, and counsel patients to save lives. Mount Sinai researchers studying a type of heart disease known as hypertrophic cardiomyopathy (HCM) ...
Computer Science and Engineering Ph.D. student Nayan Bhatia demonstrates Pulse-Fi, technology that uses WiFi signals to measure a person's heart rate. Heart rate is one of the most basic and important ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results
Feedback