Phase-field modeling offers a powerful tool for investigating the electrical control of the domain structure in ferroelectrics. However, its broad application is constrained by demanding computational ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

This study aims to assess the efficacy of machine learning models in predicting solute concentration (C) distribution in a membrane separation process, using the input parameters which are spatial ...

The biopharmaceutical industry is rapidly moving from empirical, trial and error process development toward digitalized and ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has been sharped using a machine learning technique called PRIMO. PRIMO is short ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

A machine learning (ML)-based model may aid in-hospital community-acquired pneumonia (CAP) mortality prediction, according to study findings published in Respiratory Medicine. Res ...

Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...

As artificial intelligence continues to reshape biomedical research, data-driven methods are opening new possibilities for understanding complex inflammatory ...