Tag: computational pathology

A new iScience study introduces CSCC-PAG, a deep learning framework that combines domain-specific pre-training with self-supervised domain adaptation to improve ...

A new review in the Journal of Translational Medicine finds that autonomous agentic AI systems are technically feasible in computational ...

A comprehensive review finds that while artificial intelligence shows striking performance in detecting, staging, and predicting gastric cancer outcomes, most ...

Researchers report that a data-efficient vision transformer classified lung cancer histopathology images with 98.64 percent accuracy and near-perfect AUC while ...

Researchers have developed a frequency-decoupled AI framework that nearly doubles cross-center nuclei segmentation accuracy in histopathology without requiring stain normalization ...

Researchers combined a vision transformer with a convolutional network and tuned the pair using whale- and swarm-inspired algorithms, reaching 96.27 ...

Researchers developed RIDGE, a weakly supervised deep learning system that predicts gene expression signatures and biomarkers such as microsatellite instability ...

Researchers in China have developed a neighbor-constrained attention framework that improves how artificial intelligence classifies gigapixel whole-slide pathology images by ...

Researchers have developed SlideChat, a multimodal generative AI assistant that interprets gigapixel whole-slide pathology images across 31 cancer types and ...

Researchers have developed BasNet, an open-source attention U-Net that segments axons in Bielschowsky silver-stained brain sections with accuracy that meets ...