Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...

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 ...

Bangladeshi researcher Md Masum Billah has been working to advance the application of artificial intelligence in healthcare and digital security, focusing on practical solutions for real-world ...

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 20100 ...

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 ...

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 ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

With the introduction of adaptive deep brain stimulation (aDBS) for Parkinson's disease, new questions emerge regarding who, why, and how to treat. This paper outlines the pathophysiological rationale ...

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