Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

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

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 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 ...

Bangladeshi researcher Md Masum Billah is advancing the application of artificial intelligence in healthcare and digital security, focusing on practical solutions for real-world challenges, said a ...

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

AI-powered document processing automates data extraction, classification, and validation with 95-99% accuracyMarket projected ...

Could the Innovation in Non-Human Identities Be the Key to Enhanced Secrets Security? Where progressively leaning towards automation and digital transformation, how can we ensure that the creation and ...

How Do Non-Human Identities Impact Security in a Cloud Environment? Have you ever pondered how non-human identities (NHIs) play a role? Where organizations migrate to cloud-based systems, security is ...