AI scenario planning doesn’t attempt to be “right” in the traditional forecasting sense. Its real value lies in systematic ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

Finding the right information at the right time is critical for solving complex problems. Researchers have developed an algorithm that helps individuals locate needed information more efficiently by ...

A multimodal artificial intelligence (AI) model can identify patients at risk of intimate partner violence (IPV) years before ...

Research shows that combining silica fume, fly ash, and manufactured sand in concrete significantly boosts strength and enhances predictive modeling accuracy.

The proposed approach reduces computational cost while maintaining high predictive accuracy, making it suitable for large-scale applications JEONBUK-DO, South Korea, March 16, 2026 /PRNewswire/ -- ...

Reliable and scalable water level prediction is crucial in hydrology for effective water resources management, especially ...

Explainability tools are commonly used in AI development to provide visibility into how models interpret data. In healthcare machine learning systems, explainability techniques may highlight factors ...

Machine learning algorithms may accurately predict inborn errors of immunity (IEI) in children with persistently low serum IgE.

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

Characterized by weakened or damaged heart musculature, heart failure results in the gradual buildup of fluid in a patient's lungs, legs, feet, and other parts of the body. The condition is chronic ...

A machine learning model based on electronic health record data can provide updated predictions of preeclampsia risk, ...