New AI model sets benchmark in digital pathology with superi

Researchers developed Prov-GigaPath, a whole-slide pathology foundation model using a novel vision transformer architecture. The model demonstrates superior performance in mutation prediction, cancer subtyping, and vision-language tasks. It leverages large-scale real-world data from over 30,000 patients to enhance clinical diagnostics.

Related Keywords

, Convolutional Neural Network , Long Sequence Network Longnet , Providence Gigapixel Pathology Model , Vision Transformer , Long Sequence Network , Hierarchical Image Pyramid Transformer , Contrastive Learning Based Pathology Model , Data Efficient Generalization , Self Supervised Machine Learning , Diagnostic Imaging , Cancer Genome Atlas , Simple Framework , Contrastive Learning , Visual Representations , Attention Based Multiple Instance Learning , Providence Pathology , Pan Tumor Cancer , Area Under , Receiver Operating Characteristic Curve , Precision Recall Curve , Generative Pre Trained Transformer , Multiple Instance Learning Zero Shot Transfer , Pathology Specific Language Image Pre Training , Lung Adenocarcinoma , Tumor Mutation Burden , Non Small Cell Lung Cancer , Colorectal Adenocarcinoma ,