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 ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
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.
Background Coronary microvascular dysfunction (CMD) is associated with a poor prognosis but is difficult to diagnose non-invasively. In a recent paper, ST-segment depression on exercise-ECG was found ...
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 ...
There is an emerging convergence between atherosclerotic cardiovascular disease and cancer, driven by shared risk factors and overlapping pathophysiologic mechanisms. Traditional factors, such as ...
A new study suggests that an AI-assisted blood test, which measures for biomarkers, could help to identify prediabetes risk earlier.
Adults with congenital heart disease (CHD) have a persistently high risk for cardiac reoperation, according to a new study.
Cardiometabolic syndrome arises from intricate interactions among metabolic, cardiovascular, behavioral, and environmental factors. The convergence of ...
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