Research graph
References from Early Longitudinal Changes in Radiomic Tumor Heterogeneity Predict Progression-Free Survival in Advanced Non-Small Cell Lung Cancer. Local targets link to admitted publications; unresolved targets remain external evidence.
Intra-tumour heterogeneity: A looking glass for cancer?
10.1038/nrc3261 · 2012 · External reference
The causes and consequences of genetic heterogeneity in cancer evolution
10.1038/nature12625 · 2013 · External reference
Radiomics: Extracting more information from medical images using advanced feature analysis
10.1016/j.ejca.2011.11.036 · 2012 · External reference
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
10.1038/ncomms5006 · 2014 · External reference
Radiomics: Images are more than pictures, they are data
10.1148/radiol.2015151169 · 2016 · External reference
The Image Biomarker Standardization Initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping
10.1148/radiol.2020191145 · 2020 · External reference
Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer
10.1038/s41598-017-00665-z · 2017 · External reference
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach
10.1016/j.patcog.2012.10.005 · 2013 · External reference
A new family of power transformations to improve normality or symmetry
10.1093/biomet/87.4.954 · 2000 · External reference
Cross-validatory choice and assessment of statistical predictions
10.1111/j.2517-6161.1974.tb00994.x · 1974 · External reference
Regularization and variable selection via the elastic net
10.1111/j.1467-9868.2005.00503.x · 2005 · External reference
Unresolved reference
External reference
Regression models and life-tables
10.1111/j.2517-6161.1972.tb00899.x · 1972 · External reference
Regularization paths for generalized linear models via coordinate descent
10.18637/jss.v033.i01 · 2010 · External reference
The lasso method for variable selection in the Cox model
10.1002/(sici)1097-0258(19970228)16:4<385::aid-sim380>3.0.co;2-3 · 1997 · External reference
Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
10.1002/(sici)1097-0258(19960229)15:4<361::aid-sim168>3.0.co;2-4 · 1996 · External reference
10.1007/978-1-4899-4541-9
10.1007/978-1-4899-4541-9 · External reference
Nonparametric estimation from incomplete observations
10.1080/01621459.1958.10501452 · 1958 · External reference
Evaluation of survival data and two new rank order statistics arising in its consideration
1966 · External reference
A simple sequentially rejective multiple test procedure
1979 · External reference
10.3389/fimmu.2025.1708692
10.3389/fimmu.2025.1708692 · External reference
10.1371/journal.pone.0231227
10.1371/journal.pone.0231227 · External reference
Non-invasive prediction of NSCLC immunotherapy efficacy and tumor microenvironment through unsupervised machine learning-driven CT radiomic subtypes: A multi-cohort study
10.1097/js9.0000000000002839 · 2025 · External reference
Comprehensive computed tomography radiomics analysis of lung adenocarcinoma for prognostication
10.1634/theoncologist.2017-0538 · 2018 · External reference
Radiomic phenotype features predict pathological response in non-small cell lung cancer
10.1016/j.radonc.2016.04.004 · 2016 · External reference
Pretreatment CT texture analysis for predicting survival outcomes in advanced nonsmall cell lung cancer patients receiving immunotherapy: A systematic review and meta-analysis
10.1111/1759-7714.70144 · 2025 · External reference
Predicting survival rates in brain metastases patients from non-small cell lung cancer using radiomic signatures associated with tumor immune heterogeneity
10.1002/advs.202412590 · 2025 · External reference
10.3389/fimmu.2025.1664726
10.3389/fimmu.2025.1664726 · External reference
Radiomics signature for dynamic monitoring of tumor inflamed microenvironment and immunotherapy response prediction
10.1136/jitc-2024-009140 · 2025 · External reference
Radiomics++: Review of habitat imaging analysis for decoding tumor heterogeneity
10.1146/annurev-bioeng-031825-040442 · 2026 · External reference
Vulnerabilities of radiomic signature development: The need for safeguards
10.1016/j.radonc.2018.10.027 · 2019 · External reference
Radiomics: The bridge between medical imaging and personalized medicine
10.1038/nrclinonc.2017.141 · 2017 · External reference
Repeatability and reproducibility of radiomic features: A systematic review
10.1016/j.ijrobp.2018.05.053 · 2018 · External reference
Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
10.1002/(sici)1097-0258(19960229)15:4<361::aid-sim168>3.0.co;2-4 · ExternalCitation · doi-reference
The lasso method for variable selection in the Cox model
10.1002/(sici)1097-0258(19970228)16:4<385::aid-sim380>3.0.co;2-3 · ExternalCitation · doi-reference
Predicting survival rates in brain metastases patients from non-small cell lung cancer using radiomic signatures associated with tumor immune heterogeneity
10.1002/advs.202412590 · ExternalCitation · doi-reference
10.1007/978-1-4899-4541-9
10.1007/978-1-4899-4541-9 · ExternalCitation · doi-reference
Radiomics: Extracting more information from medical images using advanced feature analysis
10.1016/j.ejca.2011.11.036 · ExternalCitation · doi-reference
Repeatability and reproducibility of radiomic features: A systematic review
10.1016/j.ijrobp.2018.05.053 · ExternalCitation · doi-reference
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach
10.1016/j.patcog.2012.10.005 · ExternalCitation · doi-reference
Radiomic phenotype features predict pathological response in non-small cell lung cancer
10.1016/j.radonc.2016.04.004 · ExternalCitation · doi-reference
Vulnerabilities of radiomic signature development: The need for safeguards
10.1016/j.radonc.2018.10.027 · ExternalCitation · doi-reference
The causes and consequences of genetic heterogeneity in cancer evolution
10.1038/nature12625 · ExternalCitation · doi-reference
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
10.1038/ncomms5006 · ExternalCitation · doi-reference
Intra-tumour heterogeneity: A looking glass for cancer?
10.1038/nrc3261 · ExternalCitation · doi-reference
Radiomics: The bridge between medical imaging and personalized medicine
10.1038/nrclinonc.2017.141 · ExternalCitation · doi-reference
Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer
10.1038/s41598-017-00665-z · ExternalCitation · doi-reference
Nonparametric estimation from incomplete observations
10.1080/01621459.1958.10501452 · ExternalCitation · doi-reference
A new family of power transformations to improve normality or symmetry
10.1093/biomet/87.4.954 · ExternalCitation · doi-reference
Non-invasive prediction of NSCLC immunotherapy efficacy and tumor microenvironment through unsupervised machine learning-driven CT radiomic subtypes: A multi-cohort study
10.1097/js9.0000000000002839 · ExternalCitation · doi-reference
Pretreatment CT texture analysis for predicting survival outcomes in advanced nonsmall cell lung cancer patients receiving immunotherapy: A systematic review and meta-analysis
10.1111/1759-7714.70144 · ExternalCitation · doi-reference
Regularization and variable selection via the elastic net
10.1111/j.1467-9868.2005.00503.x · ExternalCitation · doi-reference
Regression models and life-tables
10.1111/j.2517-6161.1972.tb00899.x · ExternalCitation · doi-reference
Cross-validatory choice and assessment of statistical predictions
10.1111/j.2517-6161.1974.tb00994.x · ExternalCitation · doi-reference
Radiomics signature for dynamic monitoring of tumor inflamed microenvironment and immunotherapy response prediction
10.1136/jitc-2024-009140 · ExternalCitation · doi-reference
Radiomics++: Review of habitat imaging analysis for decoding tumor heterogeneity
10.1146/annurev-bioeng-031825-040442 · ExternalCitation · doi-reference
Radiomics: Images are more than pictures, they are data
10.1148/radiol.2015151169 · ExternalCitation · doi-reference
The Image Biomarker Standardization Initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping
10.1148/radiol.2020191145 · ExternalCitation · doi-reference
10.1371/journal.pone.0231227
10.1371/journal.pone.0231227 · ExternalCitation · doi-reference
Comprehensive computed tomography radiomics analysis of lung adenocarcinoma for prognostication
10.1634/theoncologist.2017-0538 · ExternalCitation · doi-reference
Regularization paths for generalized linear models via coordinate descent
10.18637/jss.v033.i01 · ExternalCitation · doi-reference
10.3389/fimmu.2025.1664726
10.3389/fimmu.2025.1664726 · ExternalCitation · doi-reference
10.3389/fimmu.2025.1708692
10.3389/fimmu.2025.1708692 · ExternalCitation · doi-reference
