Related references
Note: Only part of the references are listed.Radiomics Signature as a Predictive Factor for EGFR Mutations in Advanced Lung Adenocarcinoma
Duo Hong et al.
FRONTIERS IN ONCOLOGY (2020)
Identifying relationships between imaging phenotypes and lung cancer-related mutation status: EGFR and KRAS
Gil Pinheiro et al.
SCIENTIFIC REPORTS (2020)
Classification of Severe and Critical Covid-19 Using Deep Learning and Radiomics
Cong Li et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)
CT-Based Radiomics Model for Predicting Brain Metastasis in Category T1 Lung Adenocarcinoma
Aiping Chen et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2019)
From Handcrafted to Deep-Learning-Based Cancer Radiomics Challenges and opportunities
Parnian Afshar et al.
IEEE SIGNAL PROCESSING MAGAZINE (2019)
CT imaging-based histogram features for prediction of EGFR mutation status of bone metastases in patients with primary lung adenocarcinoma
Tong-xu Shen et al.
CANCER IMAGING (2019)
CMET-04. RADIOMICS FEATURES CAN DIFFERENTIATE THE EGFR MUTATION STATUS OF BRAIN METASTASES FROM NON-SMALL CELL LUNG CANCER
Yae Won Park et al.
NEURO-ONCOLOGY (2019)
Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning
Shuo Wang et al.
EUROPEAN RESPIRATORY JOURNAL (2019)
MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis
Yiming Li et al.
EUROPEAN RADIOLOGY (2018)
A New Approach to Predict Progression-free Survival in Stage IV EGFR-mutant NSCLC Patients with EGFR-TKI Therapy
Jiangdian Song et al.
CLINICAL CANCER RESEARCH (2018)
A Radiomics Approach With CNN for Shear-Wave Elastography Breast Tumor Classification
Yongjin Zhou et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2018)
Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features
Hongyu Zhou et al.
TRANSLATIONAL ONCOLOGY (2018)
Lung adenocarcinoma: Assessment of epidermal growth factor receptor mutation status based on extended models of diffusion-weighted image
Mei Yuan et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2017)
Dynamic Contrast-enhanced MR Imaging Parameters in Bone Metastases from Non-Small Cell Lung Cancer: Comparison between Lesions with and Lesions without Epidermal Growth Factor Receptor Mutation in Primary Lung Cancer
Hyun Su Kim et al.
RADIOLOGY (2017)
A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme
Jiangwei Lao et al.
SCIENTIFIC REPORTS (2017)
Computational Radiomics System to Decode the Radiographic Phenotype
Joost J. M. van Griethuysen et al.
CANCER RESEARCH (2017)
Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer
Emmanuel Rios Velazquez et al.
CANCER RESEARCH (2017)
Radiomic Features Are Associated With EGFR Mutation Status in Lung Adenocarcinomas
Ying Liu et al.
CLINICAL LUNG CANCER (2016)
Radiogenomics of Glioblastoma: Machine Learning-based Classification of Molecular Characteristics by Using Multiparametric and Multiregional MR Imaging Features
Philipp Kickingereder et al.
RADIOLOGY (2016)
Radiomics: Images Are More than Pictures, They Are Data
Robert J. Gillies et al.
RADIOLOGY (2016)
GBM heterogeneity as a function of variable epidermal growth factor receptor variant III activity
Olle R. Lindberg et al.
ONCOTARGET (2016)
The prevalence of EGFR mutation in patients with non-small cell lung cancer: a systematic review and meta-analysis
Yue-Lun Zhang et al.
Oncotarget (2016)
Association Between Younger Age and Targetable Genomic Alterations and Prognosis in Non-Small-Cell Lung Cancer
Adrian G. Sacher et al.
JAMA ONCOLOGY (2016)
Nomograms in oncology: more than meets the eye
Vinod P. Balachandran et al.
LANCET ONCOLOGY (2015)
The Incidence of EGFR-Activating Mutations in Bone Metastases of Lung Adenocarcinoma
Pawel Krawczyk et al.
PATHOLOGY & ONCOLOGY RESEARCH (2014)
QSAR-Based Models for Designing Quinazoline/Imidazothiazoles/Pyrazolopyrimidines Based Inhibitors against Wild and Mutant EGFR
Jagat Singh Chauhan et al.
PLOS ONE (2014)
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
Hugo J. W. L. Aerts et al.
NATURE COMMUNICATIONS (2014)
Oncogenic Pathways, Molecularly Targeted Therapies, and Highlighted Clinical Trials in Non-Small-Cell Lung Cancer (NSCLC)
Thanyanan Reungwetwattana et al.
CLINICAL LUNG CANCER (2012)
Nomogram to predict the presence of EGFR activating mutation in lung adenocarcinoma
N. Girard et al.
EUROPEAN RESPIRATORY JOURNAL (2012)
Comparison of KRAS and EGFR gene status between primary non-small cell lung cancer and local lymph node metastases: implications for clinical practice
Leina Sun et al.
JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH (2011)
Bone metastasis: mechanisms and therapeutic opportunities
Larry J. Suva et al.
NATURE REVIEWS ENDOCRINOLOGY (2011)
Youden index and optimal cut-point estimated from observations affected by a lower limit of detection
Marcus D. Ruopp et al.
BIOMETRICAL JOURNAL (2008)
Selection of important variables and determination of functional form for continuous predictors in multivariable model building
Willi Sauerbrei et al.
STATISTICS IN MEDICINE (2007)
Clinical course of patients with non-small cell lung cancer and epidermal growth factor receptor exon 19 and exon 21 mutations treated with gefitinib or erlotinib
GJ Riely et al.
CLINICAL CANCER RESEARCH (2006)
EGFR mutations in lung cancer:: Correlation with clinical response to gefitinib therapy
JG Paez et al.
SCIENCE (2004)
Akaike's information criterion in generalized estimating equations
W Pan
BIOMETRICS (2001)
Share Paper
