Background Cardiovascular disease (CVD) is the leading cause of mortality worldwide, while depression is highly prevalent in this patient population and has long been regarded as an independent risk ...
Abstract: Spiking neural networks (SNNs), as the third-generation neural networks, can work under an energy efficient mode. SNNs are different from the second-generation neural networks which consume ...
Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
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 Findings of previous studies on associations between dairy consumption and metabolic health status were inconsistent. This study aimed to assess the link between consumption of dairy foods ...
Objective Unplanned hospital readmissions within 30 days of discharge measure the quality of healthcare. This study aims to ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
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