Abstract: Hypergraph Neural Networks (HGNNs) are increasingly utilized to analyze complex inter-entity relationships. Traditional HGNN systems, based on a hyperedge-centric dataflow model, ...

Detection of bottom-of-sulcus dysplasia (BOSD) is better with an automated detector combining fluorodeoxyglucose positron ...

The study identifies explainable AI as critical for bridging the gap between data-driven predictions and evidence-based ...

Abstract: With the rapid development of unmanned aerial vehicle (UAV) technology, infrared image-based object detection has garnered significant attention for applications in complex environments.

University of Arizona researchers have demonstrated that multiphoton microscopy (MPM), combined with machine learning and deep learning techniques, can accurately distinguish pancreatic neuroendocrine ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, introduced a significant development—Multi-Class Quantum Convolutional Neural Network (Quantum ...

Researchers evaluated whether a deep learning model could distinguish between autoimmune neuroinflammatory disorders based on retinal thickness.

Quantum computing is still in its early stages of development, but researchers have extensively explored its potential uses.

One of the key findings is that raw accuracy in laboratory conditions does not guarantee stability in deployment. The study ...

They are using the pattern recognition capabilities of AI to sort a cacophony of caws and rumbles and chatter into individual ...