2024
DOI: 10.1002/2056-4538.70003
|View full text |Cite
|
Sign up to set email alerts
|

Exploring prognostic biomarkers in pathological images of colorectal cancer patients via deep learning

Binshen Wei,
Linqing Li,
Yenan Feng
et al.

Abstract: Hematoxylin and eosin (H&E) whole slide images provide valuable information for predicting prognostic outcomes in colorectal cancer (CRC) patients. However, extracting prognostic indicators from pathological images is challenging due to the subtle complexities of phenotypic information. We trained a weakly supervised deep learning model on data from 640 CRC patients in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial dataset and validated it using data from 522 CRC patients in the … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 55 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?