Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer

To develop and validate a radiomics signature that can predict the clinical outcomes for patients with stage I non-small cell lung cancer (NSCLC). We retrospectively analyzed contrast-enhanced computed tomography images of patients from a training cohort (n = 147) treated with surgery and an indepen...

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Veröffentlicht in:	International journal of radiation oncology, biology, physics biology, physics, 2018-11, Vol.102 (4), p.1090-1097
Hauptverfasser:	Yu, Wen, Tang, Chad, Hobbs, Brian P., Li, Xiao, Koay, Eugene J., Wistuba, Ignacio I., Sepesi, Boris, Behrens, Carmen, Rodriguez Canales, Jaime, Parra Cuentas, Edwin Roger, Erasmus, Jeremy J., Court, Laurence E., Chang, Joe Y.
Format:	Artikel
Sprache:	eng
Schlagworte:	Aged Aged, 80 and over Carcinoma, Non-Small-Cell Lung - diagnostic imaging Carcinoma, Non-Small-Cell Lung - pathology Cohort Studies Female Humans Image Processing, Computer-Assisted - methods Lung Neoplasms - diagnostic imaging Lung Neoplasms - pathology LUNGS Machine Learning Male Middle Aged Neoplasm Staging NEOPLASMS PATIENTS RADIOLOGY AND NUCLEAR MEDICINE Tomography, X-Ray Computed VALIDATION
Online-Zugang:	Volltext
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