Science

A new deep learning framework combines longitudinal MRI scans with large language models to forecast patient outcomes and provide clearer, more interpretable insights.

A new analysis reveals how media coverage of catastrophic and violent events evolves over time, moving beyond initial reporting to focus on recovery and underlying ideologies.

A new framework leverages asynchronous learning and probability aggregation to improve disaster detection using data from diverse, unconnected devices.

A new graph neural network model leverages dual-path filtering to identify deceptive patterns in complex financial transactions.

New research shows artificial intelligence can dramatically improve the speed and accuracy of interpreting critical communications from ships in distress.

New research suggests large language models can effectively identify methodological flaws in machine learning studies, offering a path toward more reliable AI research.

A new deep learning architecture enhances the accuracy of identifying structural damage in infrastructure using image analysis.

New research reveals that machine learning models protecting Internet of Things devices are surprisingly susceptible to data poisoning, raising critical questions about their reliability in real-world security applications.

New research proposes a framework to address the critical gap between convincingly articulated answers and actual truth in AI systems, emphasizing the need for robust human-AI collaboration.

As autonomous AI systems multiply, organizations are grappling with how to understand, govern, and mitigate the risks of increasingly complex agent networks.