Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis
-
Published:2024-06
Issue:
Volume:195
Page:110266
-
ISSN:0167-8140
-
Container-title:Radiotherapy and Oncology
-
language:en
-
Short-container-title:Radiotherapy and Oncology
Author:
Hindocha SumeetORCID, Hunter BenjaminORCID, Linton-Reid Kristofer, George Charlton Thomas, Chen MitchellORCID, Logan Andrew, Ahmed Merina, Locke Imogen, Sharma Bhupinder, Doran Simon, Orton MatthewORCID, Bunce CateyORCID, Power Danielle, Ahmad Shahreen, Chan Karen, Ng Peng, Toshner RichardORCID, Yasar Binnaz, Conibear John, Murphy Ravindhi, Newsom-Davis Tom, Goodley PatrickORCID, Evison Matthew, Yousaf Nadia, Bitar George, McDonald Fiona, Blackledge Matthew, Aboagye Eric, Lee Richard
Reference51 articles.
1. Immune checkpoint inhibitor and radiotherapy-related pneumonitis: an informatics approach to determine real-world incidence, severity;Hindocha;Management, and Resource Implications Front Med (Lausanne),2021 2. From targeting the tumor to targeting the immune system: transversal challenges in oncology with the inhibition of the PD-1/PD-L1 axis;Bersanelli;World Journal of Clinical Oncology,2017 3. Advances in cancer immunotherapy 2019 - latest trends;Kruger;J Exp Clin Cancer Res,2019 4. A guide to cancer immunotherapy: from T cell basic science to clinical practice;Waldman;Nat Rev Immunol,2020 5. Management of pulmonary toxicity associated with immune checkpoint inhibitors;Delaunay;Eur Respir Rev,2019
|
|