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 ...

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, ...

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.

Clinical neurophysiology examinations include electroencephalography, sleep and vigilance studies, as well as nerve conduction recordings.

Mental health problems are among the most pressing of public health challenges, affecting millions across different age groups and societies. Depression, anxiety, and stress-related conditions rank ...

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 ...

Clinical neurophysiology examinations include electroencephalography, sleep and vigilance studies, as well as nerve conduction recordings. Interpretation of these recordings is largely taught during ...

Since arriving at Yale School of Medicine in 2019 as an internal medicine resident, Evangelos Oikonomou, MD, DPhil—now an assistant professor of medicine (cardiovascular medicine)—has focused his ...

Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...