Back to search

Article

Robust Prediction of Patient-Specific Cancer Hallmarks Using Neural Multi-Task Learning: a model development and validation study

2025-02-08

Abstract excerpt

<h4>Background: </h4> Accurate quantification of cancer hallmark activity is essential for understanding tumor progression, tailoring treatments, and improving patient outcomes. Traditional methods, such as histopathological grading and immunohistochemistry for protein expression, often overlook the complex interplay between cancer cells and the tumor microenvironment and provide limited insight into hallmark-spec...

Topics

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

Identifiers and source

Literature Corpus work
f3824c9a-d51b-5658-bb05-63d6a1c279e6
DOI
10.1101/2025.02.03.636380
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.
Robust Prediction of Patient-Specific Cancer Hallmarks Using Neural Multi-Task Learning: a model development and validation studyDOI 10.1101/2025.02.03.636380
Select a neighboring publication to make it the new centre.