Semiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the ...

Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...

More information: Xinwei Su et al, Machine learning modeling assisted intelligent process analysis for high - performance virus filtration, Journal of Membrane Science (2025). DOI: 10.1016/j ...

Biases in data can be amplified by the training process, leading to distorted — or even unjust — results. And even when a model does work, it’s not always clear why. (Deep learning algorithms are ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

A machine learning model using random forest algorithms outperforms neural networks and traditional regression in predicting tsunami early warnings for Tofino, B.C., but all models benefit from ...

Quantum machine learning (QML) is transitioning from research to practical business applications. Discover how QML is ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

Medulloblastoma the most common malignant pediatric brain tumor with a high risk of metastasis and poor survival outcomes.

Researchers at Tohoku University used machine learning potential to create large-scale models of tin (Sn) catalysts under ...

According to the Virginia Department of Health (VDH), drug overdose deaths among Virginia residents decreased by 43% in 2024.