A Machine Learning Model of Complete Response to Radiation in Rectal Cancer Reveals Immune Infiltrate and TGFβ Signalling as Key Predictors

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Domingo, E., Rathee, S., Blake, A. et al. (22 more authors) (2022) A Machine Learning Model of Complete Response to Radiation in Rectal Cancer Reveals Immune Infiltrate and TGFβ Signalling as Key Predictors. [Preprint - SSRN]

Abstract

Metadata

Item Type: Preprint
Authors/Creators:
Keywords: Rectal Neoplasms, Radiotherapy, Precision Medicine, prediction, TGF-beta, immune response, Genes
Dates:
  • Published: 17 November 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Research (LIMR) > Division of Pathology and Data Analytics
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Research (LIMR) > Division of Oncology
Funding Information:
Funder
Grant number
MRC (Medical Research Council)
MR/M016587/1
Depositing User: Symplectic Publications
Date Deposited: 30 Jul 2024 10:37
Last Modified: 30 Jul 2024 10:37
Identification Number: 10.2139/ssrn.4267509
Open Archives Initiative ID (OAI ID):

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