Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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

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

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

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 two-dimensional memories, systems that can reliably store information despite ...

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 ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

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