Development of a radiomics nomogram based on the 2D and 3D CT features to predict the survival of non-small cell lung cancer patients

2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer

(2017) Chen Shen et al.   Translational Oncology

Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer

(2017) Yucheng Zhang et al.   Scientific Reports

The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer

(2016) Peter Goldstraw et al.   Journal of Thoracic Oncology

Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non—Small Cell Lung Cancer

(2016) Yanqi Huang et al.   RADIOLOGY

Radiomics: Images Are More than Pictures, They Are Data

(2016) Robert J. Gillies et al.   RADIOLOGY

Quantitative image variables reflect the intratumoral pathologic heterogeneity of lung adenocarcinoma

(2016) E-Ryung Choi et al.   Oncotarget

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

(2015) Gary S. Collins et al.   EUROPEAN JOURNAL OF CLINICAL INVESTIGATION

Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer

(2015) Wenhua Liang et al.   JOURNAL OF CLINICAL ONCOLOGY

Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer

(2015) Chintan Parmar et al.   Scientific Reports

Machine Learning methods for Quantitative Radiomic Biomarkers

(2015) Chintan Parmar et al.   Scientific Reports

Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012

(2014) Jacques Ferlay et al.   INTERNATIONAL JOURNAL OF CANCER

Comprehensive molecular profiling of lung adenocarcinoma

(2014) Eric A. Collisson et al.   NATURE

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

(2014) Hugo J. W. L. Aerts et al.   Nature Communications

Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features

(2014) Samuel H. Hawkins et al.   IEEE Access

Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non-Small Cell Lung Cancer

(2013) T. Win et al.   CLINICAL CANCER RESEARCH

The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

(2013) Kenneth Clark et al.   JOURNAL OF DIGITAL IMAGING

MR Imaging Predictors of Molecular Profile and Survival: Multi-institutional Study of the TCGA Glioblastoma Data Set

(2013) David A. Gutman et al.   RADIOLOGY

Radiomics: Extracting more information from medical images using advanced feature analysis

(2012) Philippe Lambin et al.   EUROPEAN JOURNAL OF CANCER

EGFRmutation testing in lung cancer: a review of available methods and their use for analysis of tumour tissue and cytology samples

(2012) Gillian Ellison et al.   JOURNAL OF CLINICAL PATHOLOGY

Stability Investigations of Multivariable Regression Models Derived from Low- and High-Dimensional Data

(2011) Willi Sauerbrei et al.   Journal of Biopharmaceutical Statistics

The Impact of Additional Prognostic Factors on Survival and their Relationship with the Anatomical Extent of Disease Expressed by the 6th Edition of the TNM Classification of Malignant Tumors and the Proposals for the 7th Edition

(2010) Jean-Paul Sculier et al.   Journal of Thoracic Oncology

The International Association for the Study of Lung Cancer Staging Project: Prognostic Factors and Pathologic TNM Stage in Surgically Managed Non-small Cell Lung Cancer

(2010) Kari Chansky et al.   Journal of Thoracic Oncology

Performance Status and Smoking Status Are Independent Favorable Prognostic Factors for Survival in Non-small Cell Lung Cancer: A Comprehensive Analysis of 26,957 Patients with NSCLC

(2010) Tomoya Kawaguchi et al.   Journal of Thoracic Oncology