Researchers have built a hybrid recommender system that combines a deep denoising graph convolutional autoencoder, demographic side information, and learning...

A new graph convolution Transformer framework with self-distillation improves multi-view graph clustering by suppressing cross-view noise and exploiting complementary information...

A major review finds AI is already improving clinical trial recruitment and adjudication but warns that most applications still lack...

A new commentary in Frontiers of Digital Education argues that AI-enhanced adaptive intervention for individuals with autism should be built...

A new adaptive algorithm called SelF-Rocket dynamically selects the best input representation and pooling operator for time series classification, matching...

Researchers have developed a rough-set-based AI framework that quantifies Traditional Chinese Medicine diagnostics and fuses them with Western clinical data,...

A hybrid quantum-classical neural network with deep spatial attention has achieved 92.38 percent leakage-free accuracy in classifying skin lesions on...

Chinese researchers have unveiled a lightweight hierarchical deep learning framework that matches or beats state-of-the-art cross-domain few-shot learning methods while...

Researchers at CSIR-CCMB have developed DeNAT, a deep-learning tool that measures neurite regrowth after spinal cord injury with near-perfect agreement...

Researchers in China have developed OzoneKBNet, a retrieval-augmented AI framework that mines historical pollution episodes to deliver more accurate 48-hour...