The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...
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 ...
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 ...
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 ...
Behavior-Derived Intelligence Transforms How Recovery Is Supported, Measured, and Sustained Human behavior leaves a ...
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 ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
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