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 ...

Some cybersecurity researchers say it’s too early to worry about AI-orchestrated cyberattacks. Others say it could already be ...

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 ...

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

Please provide your email address to receive an email when new articles are posted on . Early detection and treatment of sepsis can improve outcomes for children. A team of physicians and computer ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...