Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...

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

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 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning (ML) is being used in separation science, we interviewed Emery Boston from ...

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 ...

Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness ...

Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale recurrent connectivity in the brain, we ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.