A new study in Small introduces OptiMate, a machine learning model that predicts optical properties and identifies ...

A review by researchers at Tongji University and the University of Technology Sydney published in Frontiers of Computer Science, highlights the powerful role of graph neural networks (GNNs) in ...

In sum, the data corroborate Snowflake’s assertion that its revamped go-to-market engine is landing meaningful net-new ...

While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

Learn how large language models like ChatGPT make knowledge graph creation accessible, revealing hidden connections in your ...

A team of researchers led by Niccolò Maffezzoli, "Marie Curie" fellow at Ca' Foscari University of Venice and the University of California, Irvine, and an associate member of the Institute of Polar ...

Current care in multiple sclerosis (MS) primarily relies on infrequently obtained data such as magnetic resonance imaging, clinical laboratory tests or clinical history, resulting in subtle changes ...

Enterprises should experiment with MCP where it adds value, isolate dependencies and prepare for a multi-protocol future.

Machine-learning (ML) methodologies have shown immense promise in clinical prediction, diagnosis, and decision support. Recent studies involving clinical ML ...

Somatic hypermutation (SHM) of immunoglobulin variable (V) regions modulates antibody-antigen affinity is initiated by activation-induced cytidine deaminase (AID) on single-stranded DNA (ssDNA).