Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors-Reference-Cited by-同舟云学术

Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors

Published:2024-08 Issue: Volume:106 Page:105228
ISSN:2352-3964
Container-title:eBioMedicine
language:en
Short-container-title:eBioMedicine

Author:

Domingo Enric^ORCID,Rathee Sanjay^ORCID,Blake Andrew,Samuel Leslie^ORCID,Murray Graeme,Sebag-Montefiore David,Gollins Simon,West Nicholas,Begum Rubina,Richman Susan,Quirke Phil,Redmond Keara,Chatzipli Aikaterini,Barberis Alessandro^ORCID,Hassanieh Sylvana,Mahmood Umair,Youdell Michael,McDermott Ultan,Koelzer Viktor,Leedham Simon,Tomlinson Ian,Dunne Philip,Blake Andrew,Buffa Francesca,Domingo Enric,Higgins Geoffrey,Holmes Christopher,Koelzer Viktor,Leedham Simon,Maughan Timothy,McKenna Gillies,Robineau James,Tomlinson Ian,Youdell Michael,Quirke Philip,Richman Susan,Sebag-Montefiore David,Seymour Matthew,West Nicholas,Dunne Philip,Kennedy Richard,Lawler Mark,Redmond Keara,Salto-Tellez Manuel,Campbell Peter,Chatzipli Aikaterini,Hardy Claire,McDermott Ultan,Bach Simon,Beggs Andrew,Cazier Jean-Baptiste,Middleton Gary,Morton Dion,Whalley Celina,Brown Louise,Kaplan Richard,Murray Graeme,Wilson Richard,Adams Richard,Sullivan Richard,Samuel Leslie,Harkin Paul,Walker Steven,Hill Jim,Wu Chieh-Hsi,Horgan Dennis,Buffa Francesca M.,Maughan Timothy S.^ORCID

Publisher

Elsevier BV

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1. Stratification to Neoadjuvant Radiotherapy in Rectal Cancer by Regimen and Transcriptional Signatures;Cancer Research Communications;2024-07-01