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 ...

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 ...

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

Machine Learning (ML) and Artificial Intelligence (AI) have become essential technologies across industries, automating tasks at a speed and scale far beyond human capabilities. However, building ...

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

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

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

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...