Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Microchip’s products are long-time embedded-design workhorses, and the new solutions turn its MCUs and MPUs into complete platforms for bringing secure, efficient and scalable intelligence to the edge ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

The small and complicated features of TSVs give rise to different defect types. Defects can form during any of the TSV ...

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Breakthrough AI foundation model called BrainIAC is able to predict brain age, dementia, time-to-stroke, and brain cancer ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...