Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

Bridging speed and accuracy in radiation therapy QA Led by Professor Fu Jin, the study addresses a critical challenge in ...

Model predicts effect of mutations on sequences up to 1 million base pairs in length and is adept at tackling complex ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

HOUSTON, Feb. 3, 2026 /PRNewswire/ -- Deep EigenMatics, Inc., a pioneer in high-velocity Artificial Intelligence for drug design, announced today that it has secured the #1 global ranking for new U.S.

In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...

FAYETTEVILLE, GA, UNITED STATES, January 29, 2026 /EINPresswire.com/ -- Accurate atmospheric temperature profiles are ...

A new artificial intelligence approach combines deep learning with physical modeling to extract detailed aerosol properties from complex satellite observations. By learning how light intensity and ...

AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...