首页> International journal of radiation oncology, biology, physics> 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.

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.

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第一作者： Colton,Ladbury

第一单位： Department of Radiation Oncology, City of Hope National Medical Center, Duarte, California.

作者： Colton,Ladbury ^[1] ; Richard,Li ^[2] ; Anseh,Danesharasteh ^[3] ; Zeynep,Ertem ^[3] ; Andrew,Tam ^[1] ; Jason,Liu ^[1] ; Claire,Hao ^[1] ; Rose,Li ^[1] ; Heather,McGee ^[1] ; Sagus,Sampath ^[1] ; Terence,Williams ^[1] ; Scott,Glaser ^[1] ; Mohammad,Khasawneh ^[3] ; Zhongxing,Liao ^[4] ; Percy,Lee ^[5] ; Jeff,Ryckman ^[6] ; Parvez,Shaikh ^[7] ; Arya,Amini ^[8]

作者单位： Department of Radiation Oncology, City of Hope National Medical Center, Duarte, California. ^[1] Department of Radiation Oncology, Partners in Health Whittier Hospital, Whittier, California. ^[2] Department of Systems Science and Industrial Engineering, Binghamton University, Binghamton, New York. ^[3] Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas. ^[4] Department of Radiation Oncology, City of Hope Orange County Lennar Foundation Cancer Center, Irvine, California. ^[5] Department of Radiation Oncology, West Virginia University Medicine Camden Clark Medical Center, Parkersburg, West Virginia. ^[6] Department of Radiation Oncology, West Virginia University School of Medicine, Morgantown, West Virginia. ^[7] Department of Radiation Oncology, City of Hope National Medical Center, Duarte, California. Electronic address: aamini@coh.org. ^[8]