Multivariable modeling of radiotherapy outcomes, including dose-volume and clinical factors.
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Big Data Analytics for Prostate RadiotherapyTracking of Mesenchymal Stem Cells with Fluorescence Endomicroscopy Imaging in Radiotherapy-Induced Lung Injury.A data-mining framework for large scale analysis of dose-outcome relationships in a database of irradiated head and neck cancer patients.A nomogram to predict radiation pneumonitis, derived from a combined analysis of RTOG 9311 and institutional data.Bioinformatics methods for learning radiation-induced lung inflammation from heterogeneous retrospective and prospective dataHeart irradiation as a risk factor for radiation pneumonitis.Predicting radiotherapy outcomes using statistical learning techniques.A bioinformatics approach for biomarker identification in radiation-induced lung inflammation from limited proteomics dataThe different dose-volume effects of normal tissue complication probability using LASSO for acute small-bowel toxicity during radiotherapy in gynecological patients with or without prior abdominal surgery.Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?Using multivariate regression model with least absolute shrinkage and selection operator (LASSO) to predict the incidence of Xerostomia after intensity-modulated radiotherapy for head and neck cancer.Developing Multivariable Normal Tissue Complication Probability Model to Predict the Incidence of Symptomatic Radiation Pneumonitis among Breast Cancer PatientsPatient- and therapy-related factors associated with the incidence of xerostomia in nasopharyngeal carcinoma patients receiving parotid-sparing helical tomotherapy.Predictors for Severe Acute Esophagitis in Lung Cancer Patients Treated with chemoradiotherapy: a systematic review.The Prediction of Radiotherapy Toxicity Using Single Nucleotide Polymorphism-Based Models: A Step Toward Prevention.Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC): an introduction to the scientific issues.A Bayesian network approach for modeling local failure in lung cancer.Mean esophageal radiation dose is predictive of the grade of acute esophagitis in lung cancer patients treated with concurrent radiotherapy and chemotherapyObjectively Quantifying Radiation Esophagitis With Novel Computed Tomography-Based MetricsDevelopment of multivariate NTCP models for radiation-induced hypothyroidism: a comparative analysis.Radiation dose-volume effects in the esophagusRadiation therapy following surgery for localized breast cancer: outcome prediction by classical prognostic factors and approximated genetic subtypes.Datamining approaches for modeling tumor control probability.Modeling the risk of radiation-induced acute esophagitis for combined Washington University and RTOG trial 93-11 lung cancer patientsMultivariate normal tissue complication probability modeling of gastrointestinal toxicity after external beam radiotherapy for localized prostate cancerUse of normal tissue complication probability models in the clinicLASSO NTCP predictors for the incidence of xerostomia in patients with head and neck squamous cell carcinoma and nasopharyngeal carcinoma.Radiogenomics and radiotherapy response modeling.Nomogram for radiation-induced hypothyroidism prediction in nasopharyngeal carcinoma after treatment.Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy.Bayesian network ensemble as a multivariate strategy to predict radiation pneumonitis risk.Exploring feature-based approaches in PET images for predicting cancer treatment outcomes.A genetic algorithm for variable selection in logistic regression analysis of radiotherapy treatment outcomes.Modeling plan-related clinical complications using machine learning tools in a multiplan IMRT framework.The future of predictive models in radiation oncology: from extensive data mining to reliable modeling of the results.A prognostic model comprising pT stage, N status, and the chemokine receptors CXCR4 and CXCR7 powerfully predicts outcome in neoadjuvant resistant rectal cancer patients.Regional radiation dose susceptibility within the parotid gland: effects on salivary loss and recovery.Radiomics in precision medicine for lung cancer.Experience-driven dose-volume histogram maps of NTCP risk as an aid for radiation treatment plan selection and optimization.Machine Learning in Radiation Oncology: Opportunities, Requirements, and Needs.
P2860
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P2860
Multivariable modeling of radiotherapy outcomes, including dose-volume and clinical factors.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
@wuu
2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
@zh
2006年學術文章
@zh-hant
name
Multivariable modeling of radi ...... e-volume and clinical factors.
@en
Multivariable modeling of radi ...... e-volume and clinical factors.
@nl
type
label
Multivariable modeling of radi ...... e-volume and clinical factors.
@en
Multivariable modeling of radi ...... e-volume and clinical factors.
@nl
prefLabel
Multivariable modeling of radi ...... e-volume and clinical factors.
@en
Multivariable modeling of radi ...... e-volume and clinical factors.
@nl
P2093
P1476
Multivariable modeling of radi ...... e-volume and clinical factors.
@en
P2093
Andrew Hope
Angel I Blanco
Issam El Naqa
Jeffrey Bradley
Milos Vicic
Patricia E Lindsay
P304
P356
10.1016/J.IJROBP.2005.11.022
P407
P50
P577
2006-03-01T00:00:00Z