A research team from Juntendo University in Japan wanted to find a better way to predict survival for older people with heart failure. The project was led by Professor Tetsuya Takahashi, Assistant ...
Monitoring and treating heart failure (HF) is a challenging condition at any age. Several models, such as Atrial fibrillation, Hemoglobin, Elderly, Abnormal renal parameters, Diabetes mellitus (AHEAD) ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Juntendo University researchers have trained a machine learning algorithm to use clinical information and physical function ...
In 2018, Medicare established coverage and reimbursement for its first service using artificial intelligence (AI): computed tomography (CT) fractional flow reserve (FFRCT). FFRCT is used in ...
Adults with congenital heart disease (CHD) have a persistently high risk for cardiac reoperation, according to a new study.
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 ...
Background Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial ...
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 ...
Furthermore, our findings can be compared with recent NHANES-based machine learning studies, in which LightGBM and SHAP were applied to evaluate the association between the visceral fat metabolism ...
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