Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

Published in Microplastics, the study titled “Canonical Spectral Transformation for Raman Spectra Enables High Accuracy AI Identification of Marine Microplastics” introduces a novel data processing ...

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

The models are designed to predict someone’s risk of diabetes or stroke. A few might already have been used on patients.

Rice University researchers develop method to generate training data for AI protein language programs to predict ...

Enterprises face challenges in preparing data for generative AI due to data quality and accessibility issues. Gartner ...

Running a single physics simulation can take hours or days, depending on the complexity of the geometry and the equations ...

Should U.S. Supreme Court Justices be sharing their views about AI? Some say yes, others insist no. I discuss the matter and ...

Numbers are the language of science—yet in research articles, they are often buried within the text and difficult to analyze.

In an era defined by rapid AI adoption, securing software has become increasingly complex. As organizations integrate ...