The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
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 ...
The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human ...
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 ...
A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...
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 ...
Behavior-Derived Intelligence Transforms How Recovery Is Supported, Measured, and Sustained Human behavior leaves a ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
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