Article

Molecularly informed analysis of histopathology images using natural language

2025-07-18

Abstract excerpt

Histopathology refers to the microscopic examination of diseased tissues and routinely guides treatment decisions for cancer and other diseases. Currently, this analysis focuses on morphological features but rarely considers gene expression information, which can add an important molecular dimension. Here, we introduce SpotWhisperer, an AI method that links histopathological images to spatial gene expression profi...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 45960d44-60ef-5570-9a9a-e18a34b93132
DOI: 10.1101/2025.07.14.664402

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Molecularly informed analysis of histopathology images using natural languageDOI 10.1101/2025.07.14.664402Read

H2O: A Foundation Model Bridging Histopathology to Spatial Multi-Omics ProfilingSemantic proximity Read

SpatialFinder: A Human-in-the-Loop Vision-Language Framework for Prioritizing High-Value Regions in Spatial TranscriptomicsSemantic proximity Read

Agent SPI-WSI: In context learning for computationally spatial pathway inferring on whole slide histopathology images conditioned on bulk RNA sequencing using pathologist in the loopSemantic proximity Read

Query-driven generative AI synthesizes multi-modal spatial omics from histologySemantic proximity Read

HistAgent: an evidence-grounded agent for spatial molecular reasoning from routine histologySemantic proximity Read

Web engine for tumor pathology image retrievals on massive scalesSemantic proximity Read

Generating clinical-grade pathology reports from gigapixel whole slide images with HistoGPTSemantic proximity Read

spEMO: Leveraging Multi-Modal Foundation Models for Analyzing Spatial Multi-Omic and Histopathology DataSemantic proximity Read

Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes.Semantic proximity Read

Dense, high-resolution mapping of cells and tissues from pathology images for the interpretable prediction of molecular phenotypes in cancerSemantic proximity Read

spEMO: Leveraging Multi-Modal Foundation Models for Analyzing Spatial Multi-Omic and Histopathology DataSemantic proximity Read

SlideFlame: A data-efficient vision-language model for anatomically grounded pathology reportingSemantic proximity Read