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 ...

This article examines the work of data scientist Sai Prashanth Pathi in AI for credit risk, focusing on explainable machine ...

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 ...

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

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

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

Introduction In an era where data breaches and cyber threats are on the rise, organizations are seeking advanced solutions to ...

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 ...

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.