Back to search

Article

Translating Histopathology Foundation Model Embeddings into Cellular and Molecular Features for Clinical Studies

2026-03-19

Abstract excerpt

AI-powered pathology foundation models provide general-purpose representations of histopathological images by encoding image tiles into numerical embeddings. However, these embeddings are not directly interpretable in biological or clinical terms and must be translated into biologically meaningful features, such as cell-type composition or gene expression, to enable downstream clinical applications. To bridge this...

Topics

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

Identifiers and source

Literature Corpus work
e9bb7b53-7e40-5a71-827a-21f8b1fe6964
DOI
10.64898/2026.03.17.711896
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Translating Histopathology Foundation Model Embeddings into Cellular and Molecular Features for Clinical StudiesDOI 10.64898/2026.03.17.711896
Select a neighboring publication to make it the new centre.