The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

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 ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 possible variants—more combinations than atoms in the observable universe.

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 ...

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 ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

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

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...