Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

What if the Higgs boson found in 2012 is not alone but is the only sibling we have encountered so far? Scientists at CERN ...

A large study found that a LightGBM machine learning model accurately predicted survival and early death risk in patients ...

Researchers developed a two-stage machine learning framework that detected diabetes and classified records as prediabetes, ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

The Martin-Hopkins equation to assess low-density lipoprotein (LDL) cholesterol levels in blood samples has been used by laboratories in the U.S. and other countries to guide efforts to lower ...

Medical AI diagnostic accuracy can appear excellent on benchmarks while the model exploits physicians' test-ordering habits ...

Physics-informed machine learning connects atomic structure with ion transport and electrolyte stability, accelerating better sodium- and lithium-ion batteries.

Nvidia's (NVDA-3.55%) hardware made a name for itself in powering high-end video game graphics, but in recent years, the ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...