Back to search

Article

Weak supervision of H&E slides reveals systems-level biology and functional states that govern therapeutic resistance

2026-05-08

Abstract excerpt

<h4>ABSTRACT</h4> Precision oncology lacks scalable tools to assess, at the patient level, systems-level tumor microenvironment (TME) programs driving therapeutic resistance. To address this gap, we trained a weakly-supervised deep learning model, using routine H&E slides as input, to derive quantitative activity for therapeutically-relevant TME phenotypes, spanning immune, metabolic, and tumor cell-intrinsic pro...

Topics

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

Identifiers and source

Literature Corpus work
ca8d525a-6b3d-5537-9816-aaffd7afa548
DOI
10.64898/2026.05.05.723013
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.
Weak supervision of H&E slides reveals systems-level biology and functional states that govern therapeutic resistanceDOI 10.64898/2026.05.05.723013
Select a neighboring publication to make it the new centre.