Discriminating survival outcomes in patients with glioblastoma using a simulation-based, patient-specific response metric - Wikidata - awgldk - TriplyDB

Discriminating survival outcomes in patients with glioblastoma using a simulation-based, patient-specific response metric

Discriminating survival outcomes in patients with glioblastoma using a simulation-based, patient-specific response metric

http://www.wikidata.org/entity/Q34570841

about

Patient-specific mathematical neuro-oncology: using a simple proliferation and invasion tumor model to inform clinical practice The Force at the Tip--Modelling Tension and Proliferation in Sprouting Angiogenesis Towards the Personalized Treatment of Glioblastoma: Integrating Patient-Specific Clinical Data in a Continuous Mechanical Model Predicting in vivo glioma growth with the reaction diffusion equation constrained by quantitative magnetic resonance imaging data.Invasion and proliferation kinetics in enhancing gliomas predict IDH1 mutation status.Gene therapy enhances chemotherapy tolerance and efficacy in glioblastoma patients Assessment and treatment relevance in elderly glioblastoma patients.Patient-specific metrics of invasiveness reveal significant prognostic benefit of resection in a predictable subset of gliomas Toward patient-specific, biologically optimized radiation therapy plans for the treatment of glioblastoma.Toward a science of tumor forecasting for clinical oncology.From patient-specific mathematical neuro-oncology to precision medicine Image based modeling of tumor growth.A Proposed Paradigm Shift in Initializing Cancer Predictive Models with DCE-MRI Based PK Parameters: A Feasibility Study.In silico analysis suggests differential response to bevacizumab and radiation combination therapy in newly diagnosed glioblastoma.3D Mathematical Modeling of Glioblastoma Suggests That Transdifferentiated Vascular Endothelial Cells Mediate Resistance to Current Standard-of-Care Therapy.Chemotherapeutic Dose Scheduling Based on Tumor Growth Rates Provides a Case for Low-Dose Metronomic High-Entropy Therapies.The biology and mathematical modelling of glioma invasion: a review.Mathematical model of perineural tumor spread: a pilot study.Clinical implications of in silico mathematical modeling for glioblastoma: a critical review.Expert-validated CSF segmentation of MNI atlas enhances accuracy of virtual glioma growth patterns.

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P2860

Discriminating survival outcomes in patients with glioblastoma using a simulation-based, patient-specific response metric

http://www.wikidata.org/entity/Q34570841

description

2013 nî lūn-bûn

@nan

2013 թուականի Յունուարին հրատարակուած գիտական յօդուած

@hyw

2013 թվականի հունվարին հրատարակված գիտական հոդված

@hy

2013年の論文

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2013年論文

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2013年論文

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2013年論文

@zh-hk

2013年論文

@zh-mo

2013年論文

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2013年论文

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name

Discriminating survival outcom ...... tient-specific response metric

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Discriminating survival outcom ...... tient-specific response metric

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Discriminating survival outcom ...... tient-specific response metric

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type

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Discriminating survival outcom ...... tient-specific response metric

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Discriminating survival outcom ...... tient-specific response metric

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Discriminating survival outcom ...... tient-specific response metric

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prefLabel

Discriminating survival outcom ...... tient-specific response metric

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Discriminating survival outcom ...... tient-specific response metric

@en

Discriminating survival outcom ...... tient-specific response metric

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JOURNAL.PONE.0051951

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Discriminating survival outcom ...... tient-specific response metric

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Albert Lai

http://www.w3.org/2001/XMLSchema#string

Anne L Baldock

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Carly A Bridge

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Jason K Rockhill

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Kristin R Swanson

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Maciej M Mrugala

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Rita Sodt

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Sunyoung Ahn

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Timothy F Cloughesy

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Tyler Cloke

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P2860

An integrated genomic analysis of human glioblastoma multiforme

New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)

Promising survival for patients with newly diagnosed glioblastoma multiforme treated with concomitant radiation plus temozolomide followed by adjuvant temozolomide.

Pseudoprogression and pseudoresponse in the treatment of gliomas.

Current progress in patient-specific modeling.

Pseudoprogression and pseudoresponse: imaging challenges in the assessment of posttreatment glioma.

Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion.

A mathematical modelling tool for predicting survival of individual patients following resection of glioblastoma: a proof of principle

The evolution of mathematical modeling of glioma proliferation and invasion.

Quantitative metrics of net proliferation and invasion link biological aggressiveness assessed by MRI with hypoxia assessed by FMISO-PET in newly diagnosed glioblastomas

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e51951

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scholarly article

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10.1371/JOURNAL.PONE.0051951

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1

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Andrew D Trister

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2013-01-23T00:00:00Z

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234905161

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23372647

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3553125

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