Machine learning has moved past its initial experimental phase. In earlier years, development often focused on creating the largest possible models to see what capabilities might appear. Today, the ...

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. To address this need, a team of researchers led by the ...

Protein engineering is a field primed for artificial intelligence research. Each protein is made up of amino acids; to ...

Background and Goal: This study examined whether machine learning could predict the risk and contributing factors of no-shows and late cancellations in primary care practices. Study Approach: ...

AI-driven interventions reduce the odds of hospitalization within 7 days by 8% in patients with end-stage kidney disease receiving hemodialysis, according to a recent study.