An AI-powered model developed at University of Michigan can read a brain MRI and diagnose a person in seconds, a study suggests.

Severe bleeding is one of the most common and preventable causes of death after traumatic injury, yet currently available tools have poor ability to determine which patients urgently need blood ...

New research shows that the use of an AI-enabled digital stethoscope more than doubled the identification of moderate to severe valvular heart disease during routine clinical examinations, compared to ...

Award-winning presentation recognizes AI-CVD-HF heart failure prediction model leveraging coronary artery calcium (CAC) scans HONG KONG, January 27, 2026 /EINPresswire.com/ — HeartLung AI announced ...

People who brought their blood glucose down to a normal level had a lower risk of death from heart disease or hospitalization for heart failure after 20 years. By Nina Agrawal People with prediabetes ...

“I’ll worry about my heart health when I’m older.” That may be too late, doctors warn. While the average age for being diagnosed with heart disease in the United States is typically in the mid-60s for ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

Smart health refers to the integration of cutting-edge technologies into healthcare systems to improve patient care and apply intelligent clinical decision-making. The study investigates how ...

Please provide your email address to receive an email when new articles are posted on . Machine learning can use patient-reported outcomes to identify low disease activity in rheumatoid arthritis.

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Abstract: This Study will explore how the IoT and machine learning predict heart disease risks through real-time wearable device and sensor data. The Cleveland and Hungarian datasets have relevant ...