Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Objective Unplanned hospital readmissions within 30 days of discharge measure the quality of healthcare. This study aims to ...
Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Objective To investigate the associations of oxidative balance score (OBS) with all-cause mortality, cardiovascular mortality and cardiovascular disease (CVD) incidence in two large, population-based ...
Introduction Cerebral palsy (CP) is a non-progressive condition involving movement and muscle tone difficulties due to injury to the developing brain. Most cases arise around birth, but a smaller ...
Background As the threat of child malnutrition increases, the focus remains mostly on short-term consequences. Long-term ...
A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.
A home blood pressure telemonitoring (HBPT) program effectively reduced BP in real-world clinical settings, but its enrollment expenses increased overall costs. The HBPT program reduced BP clinic ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results