The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

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 ...

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 ...

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

Behavior-Derived Intelligence Transforms How Recovery Is Supported, Measured, and Sustained Human behavior leaves a ...