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 ...
The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
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 ...
Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human ...
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 ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results