Predicting distant failure in early stage NSCLC treated with SBRT using clinical parametersPredicting distant failure in lung SBRT

Radiotherapy and Oncology

Volumn 119, Issue 3, 2016, Pages 501-504

  Zhou, Zhiguo ^a   Folkert, Michael ^a   Cannon, Nathan ^a   Iyengar, Puneeth ^a   Westover, Kenneth ^a   Zhang, Yuanyuan ^a   Choy, Hak ^a   Timmerman, Robert ^a   Yan, Jingsheng ^b   Xie, Xian J ^b   Jiang, Steve ^a   Wang, Jing ^a  

^a UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

^b UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

Author keywords

Clinical parameter; Distant failure; Feature selection; Machine learning; SBRT

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER STAGING; EARLY CANCER; HUMAN; LOGISTIC REGRESSION ANALYSIS; MACHINE LEARNING; MAJOR CLINICAL STUDY; MEASUREMENT ACCURACY; NON SMALL CELL LUNG CANCER; OUTCOME ASSESSMENT; PREDICTIVE VALUE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STEREOTACTIC BODY RADIATION THERAPY; SUPPORT VECTOR MACHINE; TREATMENT FAILURE; AGED; AREA UNDER THE CURVE; CARCINOMA, NON-SMALL-CELL LUNG; FEMALE; LUNG NEOPLASMS; MALE; MIDDLE AGED; PATHOLOGY; RADIOSURGERY; STATISTICAL MODEL;

AGED; ALGORITHMS; AREA UNDER CURVE; CARCINOMA, NON-SMALL-CELL LUNG; FEMALE; HUMANS; LOGISTIC MODELS; LUNG NEOPLASMS; MALE; MIDDLE AGED; NEOPLASM STAGING; NEURAL NETWORKS (COMPUTER); RADIOSURGERY; TREATMENT FAILURE;

EID: 84965017496     PISSN: 01678140     EISSN: 18790887     Source Type: Journal    
DOI: 10.1016/j.radonc.2016.04.029     Document Type: Article

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