A machine learning model predicted cardiac tamponade during AF ablation with high accuracy. Learn how XGBoost may improve ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Trend-following funds, which use quantitative models and algorithms to trade market moves, have traversed the recent wild swings in gold and silver.

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Social media algorithms determine what billions of users see daily, yet most creators barely scratch the surface of how they operate. Platforms prioritize content ranking using engagement metrics, ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

AI-powered overclocking uses machine learning to boost CPU and GPU performance safely in 2026, delivering higher FPS, better efficiency, and automatic stability.

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, ...