https://doi.org/10.7490/f1000research.1119682.1
Poster
NOT PEER REVIEWED
Download
metrics
VIEWS
401
 
downloads
25
CITE
How to cite this poster:
Azher ZL, Nithilaselvan S, DeVictor T et al. Preliminary multimodal deep learning investigation of tumor immune microenvironment cell-type deconvolution for colorectal cancer prognostication  [version 1; not peer reviewed]. F1000Research 2023, 12:1559 (poster) (https://doi.org/10.7490/f1000research.1119682.1)
NOTE: it is important to ensure the information in square brackets after the title is included in this citation.

Preliminary multimodal deep learning investigation of tumor immune microenvironment cell-type deconvolution for colorectal cancer prognostication 

Zarif L Azher, Salban Nithilaselvan, Tristan DeVictor, Eric Zhang, Tanay Panja, Ji-Qing Chen, Brock Christensen, Lucas Salas, Louis Vaickus, Joshua Levy1
Author Affiliations
  • Metrics
  • 401 Views
  • 25 Downloads
 
Browse by related subjects
Published 05 Dec 2023

Preliminary multimodal deep learning investigation of tumor immune microenvironment cell-type deconvolution for colorectal cancer prognostication 

[version 1; not peer reviewed]

Zarif L Azher, Salban Nithilaselvan, Tristan DeVictor, Eric Zhang, Tanay Panja, Ji-Qing Chen, Brock Christensen, Lucas Salas, Louis Vaickus, Joshua Levy1
Author Affiliations
1 Departments of Pathology and Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, California, USA
Presented at
Pacific Symposium on Biocomputing (PSB), 2024
Abstract
Competing Interests

No competing interests were disclosed

Keywords
tumor immune microenvironment, multimodal, prognostication, cell type deconvolution, whole slide imaging
Comments
0 Comments
 
Sign In
If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password.

The email address should be the one you originally registered with F1000.

Email address not valid, please try again

You registered with F1000 via Google, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Google account password, please click here.

You registered with F1000 via Facebook, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Facebook account password, please click here.

Code not correct, please try again
Email us for further assistance.
Server error, please try again.