Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

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

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

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 ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...

New Wireless Broadband Alliance report lays out the frameworks and priorities needed to scale intelligent Wi-Fi without ...

Zero knowledge proofs enhance transparency while maintaining confidentiality in decision-making processes. Lagrange is ...

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 ...

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

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