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.

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been developed. This ...

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 ...

EDN announces this year’s winners of the Electronic Products Product of the Year Awards, selected by the editors.

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...

Background and objectives Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.

Researchers at UMass Lowell have uncovered an innovative way to spot Alzheimer’s disease long before the first official ...

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 ...