Explainable Artificial Intelligence to Identify Dosimetric Predictors of Toxicity in Patients with Locally Advanced Non-Small Cell Lung Cancer: A Secondary Analysis of RTOG 0617-Reference-Cited by-同舟云学术

Explainable Artificial Intelligence to Identify Dosimetric Predictors of Toxicity in Patients with Locally Advanced Non-Small Cell Lung Cancer: A Secondary Analysis of RTOG 0617

Published:2023-12 Issue:5 Volume:117 Page:1287-1296
ISSN:0360-3016
Container-title:International Journal of Radiation Oncology*Biology*Physics
language:en
Short-container-title:International Journal of Radiation Oncology*Biology*Physics

Author:

Ladbury Colton^ORCID,Li Richard,Danesharasteh Anseh,Ertem Zeynep,Tam Andrew,Liu Jason,Hao Claire,Li Rose,McGee Heather,Sampath Sagus,Williams Terence,Glaser Scott,Khasawneh Mohammad,Liao Zhongxing,Lee Percy,Ryckman Jeff,Shaikh Parvez,Amini Arya^ORCID

Funder

National Cancer Institute

Eli Lilly and Company

Publisher

Elsevier BV

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology,Radiation

Reference26 articles.

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2. Long-term results of NRG Oncology RTOG 0617: Standard- versus high-dose chemoradiotherapy with or without cetuximab for unresectable stage III non–small-cell lung cancer;Bradley;J Clin Oncol,2020

3. Standard-dose versus high-dose conformal radiotherapy with concurrent and consolidation carboplatin plus paclitaxel with or without cetuximab for patients with stage IIIA or IIIB non-small-cell lung cancer (RTOG 0617): a randomised, two-by-two factorial phase 3 study

4. Impact of intensity-modulated radiation therapy technique for locally advanced non–small-cell lung cancer: A secondary analysis of the NRG Oncology RTOG 0617 randomized clinical trial;Chun;J Clin Oncol,2017

5. Modeling the impact of cardiopulmonary irradiation on overall survival in NRG Oncology Trial RTOG 0617;Thor;Clin Cancer Res,2020

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