Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...