Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

The size of Amazon Ads is staggering, with billions of impressions in categories such as fashion, fitness, and luxury. I have ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

A publicly available AI tool correctly predicted approximately twice as many children with acute lymphoblastic leukemia who would relapse as three expert clinicians.XGBoost, a boosting algorithm, had ...

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 ...

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...

Machine-learning hedge funds surged on the recent jump in precious metals prices, before sidestepping last week's sell-off. Also known as commodity trading advisors (CTAs), the sector notched up one ...

ACGRIME is an improved metaheuristic algorithm derived from the original RIME framework. ACGRIME integrates three strategic mechanisms: chaotic initialization, adaptive weighting and Gaussian mutation ...