Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

TCTMD spoke with Lior Jankelson, MD, PhD (NYU Langone Health, New York, NY), an electrophysiologist who leads the AI/machine ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Researchers led by Min Zhang and Dabao Zhang of the University of California, Irvine's Joe C. Wen School of Population & ...

A new international study suggests most clinical artificial intelligence (AI) tools are not yet ready for safe, equitable use ...

There is an emerging convergence between atherosclerotic cardiovascular disease and cancer, driven by shared risk factors and overlapping pathophysiologic mechanisms. Traditional factors, such as ...

Hypertension is the leading risk factor for cardiovascular disease, the most common cause of death worldwide. Less than half the people with high blood pressure are aware of their diagnosis, and only ...

Although the AI-supported stethoscope shows promise, both studies highlight further research across more diverse clinical environments and populations is necessary. Additionally, while the AI ...