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Predicting outcomes in radiation oncology--multifactorial decision support systems

Predicting outcomes in radiation oncology--multifactorial decision support systems

http://www.wikidata.org/entity/Q36014711

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Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach Big Data Analytics for Prostate Radiotherapy Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets ENT COBRA (Consortium for Brachytherapy Data Analysis): interdisciplinary standardized data collection system for head and neck patients treated with interventional radiotherapy (brachytherapy)Imaging techniques for tumour delineation and heterogeneity quantification of lung cancer: overview of current possibilities Characterization of tumor heterogeneity using dynamic contrast enhanced CT and FDG-PET in non-small cell lung cancer International data-sharing for radiotherapy research: an open-source based infrastructure for multicentric clinical data mining Technology for Innovation in Radiation Oncology Point/Counterpoint. Future radiotherapy practice will be based on evidence from retrospective interrogation of linked clinical data sources rather than prospective randomized controlled clinical trials.Rapid learning in practice: a lung cancer survival decision support system in routine patient care data Standardized data collection to build prediction models in oncology: a prototype for rectal cancer.Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data.Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT Grading of Gliomas by Using Radiomic Features on Multiple Magnetic Resonance Imaging (MRI) Sequences.CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer.Toward better benchmarking: challenge-based methods assessment in cancer genomics.Systematic analysis of 18F-FDG PET and metabolism, proliferation and hypoxia markers for classification of head and neck tumors Ensemble analyses improve signatures of tumour hypoxia and reveal inter-platform differences.Prospective, longitudinal, multi-modal functional imaging for radical chemo-IMRT treatment of locally advanced head and neck cancer: the INSIGHT study.Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer.The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis.Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability Machine Learning methods for Quantitative Radiomic Biomarkers.Personalization and Patient Involvement in Decision Support Systems: Current Trends Repeatability of hypoxia PET imaging using [¹⁸F]HX4 in lung and head and neck cancer patients: a prospective multicenter trial Decoding Tumor Phenotypes for ALK, ROS1, and RET Fusions in Lung Adenocarcinoma Using a Radiomics Approach Assessing Agreement between Radiomic Features Computed for Multiple CT Imaging Settings.Personalized radiotherapy: concepts, biomarkers and trial design Different prognostic models for different patient populations: validation of a new prognostic model for patients with oropharyngeal cancer in Western Europe.Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer.Radiation-induced CD8 T-lymphocyte Apoptosis as a Predictor of Breast Fibrosis After Radiotherapy: Results of the Prospective Multicenter French Trial.Validation of a rectal cancer outcome prediction model with a cohort of Chinese patients.Uncertainty analysis of quantitative imaging features extracted from contrast-enhanced CT in lung tumors.A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology.A prospective study comparing the predictions of doctors versus models for treatment outcome of lung cancer patients: a step toward individualized care and shared decision making.Understanding the tumor microenvironment and radioresistance by combining functional imaging with global gene expression.Implementation of a rapid learning platform: Predicting 2-year survival in laryngeal carcinoma patients in a clinical setting.

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Predicting outcomes in radiation oncology--multifactorial decision support systems

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Nature Reviews Clinical Oncology

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Predicting outcomes in radiation oncology--multifactorial decision support systems

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Vincenzo Valentini

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P2860

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

Prognostic effect size of cardiovascular biomarkers in datasets from observational studies versus randomised trials: meta-epidemiology study

International network of cancer genome projects.

Variants at 6q21 implicate PRDM1 in the etiology of therapy-induced second malignancies after Hodgkin's lymphoma

Identification of noninvasive imaging surrogates for brain tumor gene-expression modules

Need for standardization of 18F-FDG PET/CT for treatment response assessments

Unique microRNA molecular profiles in lung cancer diagnosis and prognosis

Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Identification of selective inhibitors of cancer stem cells by high-throughput screening

Exploring the role of cancer stem cells in radioresistance

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