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 ...

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

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

The Opioid Risk Tool for Opioid Use Disorder may help identify patients with chronic noncancer pain at increased risk for OUD ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

New AI model decodes brain signals captured noninvasively via EEG opens the possibility of developing future neuroprosthetics ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

A novel multi-task XGBoost model shows robust overall performance in predicting antimicrobial resistance in common gram-negative pathogens.

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Stock markets are essential for households for wealth creation and for firms for raising financial resources for capacity ...

Early Risk Signals: Credit Card Delinquency Watch - AI-powered predictive analytics for proactive credit risk management. Machine learning models (Random Forest & Gradient Boosting) analyze behavioral ...