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 ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

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 ...

Wilmington, Delaware - February 03, 2026 - PRESSADVANTAGE - PSCI shared perspective on staffing and consulting ...

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 ...

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 ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

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 ...