Back to search

Article

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features

2020-11-04

Abstract excerpt

Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis generated with such models is often confounded by the presence of host cells and can give rise to data misinterpretation. For instance, it is important to discriminat...

Topics

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

Identifiers and source

Literature Corpus work
c167fae2-15ed-5adf-a898-459cca9d88e7
DOI
10.1101/2020.11.03.361741
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.
Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual FeaturesDOI 10.1101/2020.11.03.361741
Select a neighboring publication to make it the new centre.