Incorporating marble dust and polypropylene fibers in concrete boosts strength and durability, highlighting the role of machine learning in mix optimization.

Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer's disease with nearly 93% accuracy.

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...

For years, the Prairie Pothole Region has bothered me in a very specific way. On a map, it looks like a normal landscape: ...

A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...

Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new ...

Researchers at the University of Bath have developed the first artificial intelligence (AI) tool that predicts the carbon ...

More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from ...

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...

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