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Tumor growth model of ductal carcinoma: from in situ phase to stroma invasion

Journal of theoretical biology, 2017-09, Vol.429, p.253-266

2017

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Intensity harmonization techniques influence radiomics features and radiomics-based predictions in sarcoma patients

Scientific reports, 2020-09, Vol.10 (1), p.15496-15496, Article 15496

2020

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Improved 18-FDG PET/CT diagnosis of multiple myeloma diffuse disease by radiomics analysis

Nuclear medicine communications, 2021-10, Vol.42 (10), p.1135

2021

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Computational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme

PloS one, 2016-01, Vol.11 (1), p.e0146617-e0146617

2016

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A Model-Strengthened Imaging Biomarker for Survival Prediction in EGFR-Mutated Non-small-cell Lung Carcinoma Patients Treated with Tyrosine Kinase Inhibitors

Bulletin of mathematical biology, 2021-06, Vol.83 (6), p.68-68, Article 68

2021

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Computational Modelling of Metastasis Development in Renal Cell Carcinoma

PLoS computational biology, 2015-11, Vol.11 (11), p.e1004626-e1004626

2015

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Differentiation of Small Clear Renal Cell Carcinoma and Oncocytoma through Magnetic Resonance Imaging-Based Radiomics Analysis: Toward the End of Percutaneous Biopsy

Journal of personalized medicine, 2023-09, Vol.13 (10), p.1444

2023

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Effects of anti-angiogenesis on glioblastoma growth and migration: model to clinical predictions

PloS one, 2014-12, Vol.9 (12), p.e115018

2014

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Radiomics and Machine Learning in Anal Squamous Cell Carcinoma: A New Step for Personalized Medicine?

Applied sciences, 2020-03, Vol.10 (6), p.1988

2020

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Ion fluxes, transmembrane potential, and osmotic stabilization: a new dynamic electrophysiological model for eukaryotic cells

European biophysics journal, 2011-03, Vol.40 (3), p.235-246

2011

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Systematic review of sarcomas radiomics studies: Bridging the gap between concepts and clinical applications?

European journal of radiology, 2020-11, Vol.132, p.109283-109283, Article 109283

2020

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T 2 -based MRI Delta-radiomics improve response prediction in soft-tissue sarcomas treated by neoadjuvant chemotherapy

Journal of magnetic resonance imaging, 2019-08, Vol.50 (2), p.497-510

2019

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High‐Grade Soft‐Tissue Sarcomas: Can Optimizing Dynamic Contrast‐Enhanced MRI Postprocessing Improve Prognostic Radiomics Models?

Journal of magnetic resonance imaging, 2020-07, Vol.52 (1), p.282-297

2020

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Influence of temporal parameters of DCE‐MRI on the quantification of heterogeneity in tumor vascularization

Journal of magnetic resonance imaging, 2019-12, Vol.50 (6), p.1773-1788

2019

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Joint State-Parameter Estimation for Tumor Growth Model

SIAM journal on applied mathematics, 2021-01, Vol.81 (2), p.355-377

2021

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T2‐based MRI Delta‐radiomics improve response prediction in soft‐tissue sarcomas treated by neoadjuvant chemotherapy

Journal of magnetic resonance imaging, 2019-08, Vol.50 (2), p.497-510

2019

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Evaluation of four tumour growth models to describe the natural history of meningiomas

EBioMedicine, 2023-08, Vol.94, p.104697-104697, Article 104697

2023

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Evaluation of four tumour growth models to describe the natural history of meningiomasResearch in context

EBioMedicine, 2023-08, Vol.94, p.104697

2023

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Spatial mechanistic modeling for prediction of the growth of asymptomatic meningiomas

Computer methods and programs in biomedicine, 2021-02, Vol.199, p.105829-105829, Article 105829

2021

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A Multilayer Grow-or-Go Model for GBM: Effects of Invasive Cells and Anti-Angiogenesis on Growth

Bulletin of mathematical biology, 2014-09, Vol.76 (9), p.2306-2333

2014

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Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19

European radiology, 2023-12, Vol.33 (12), p.9262-9274

2023

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Abstract B2-18: Mechanisms of GBM progression on bevacizumab: Model predictions

Cancer research (Chicago, Ill.), 2015-11, Vol.75 (22_Supplement_2), p.B2-B2-18

2015

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Computational Modeling of Solid Tumor Growth: The Avascular Stage

SIAM journal on scientific computing, 2010-01, Vol.32 (4), p.2321-2344

2010

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Spatial mechanistic modeling for prediction of the growth of asymptomatic meningioma

Computer methods and programs in biomedicine, 2020

2020

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Tumor growth model of ductal carcinoma: from in situ phase to stroma invasion

Intensity harmonization techniques influence radiomics features and radiomics-based predictions in sarcoma patients

Improved 18-FDG PET/CT diagnosis of multiple myeloma diffuse disease by radiomics analysis

Computational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme

A Model-Strengthened Imaging Biomarker for Survival Prediction in EGFR-Mutated Non-small-cell Lung Carcinoma Patients Treated with Tyrosine Kinase Inhibitors

Computational Modelling of Metastasis Development in Renal Cell Carcinoma

Differentiation of Small Clear Renal Cell Carcinoma and Oncocytoma through Magnetic Resonance Imaging-Based Radiomics Analysis: Toward the End of Percutaneous Biopsy

Effects of anti-angiogenesis on glioblastoma growth and migration: model to clinical predictions

Radiomics and Machine Learning in Anal Squamous Cell Carcinoma: A New Step for Personalized Medicine?

MRI-Based Radiomics Input for Prediction of 2-Year Disease Recurrence in Anal Squamous Cell Carcinoma

Ion fluxes, transmembrane potential, and osmotic stabilization: a new dynamic electrophysiological model for eukaryotic cells

Systematic review of sarcomas radiomics studies: Bridging the gap between concepts and clinical applications?

T 2 -based MRI Delta-radiomics improve response prediction in soft-tissue sarcomas treated by neoadjuvant chemotherapy

High‐Grade Soft‐Tissue Sarcomas: Can Optimizing Dynamic Contrast‐Enhanced MRI Postprocessing Improve Prognostic Radiomics Models?

Influence of temporal parameters of DCE‐MRI on the quantification of heterogeneity in tumor vascularization

Joint State-Parameter Estimation for Tumor Growth Model

T2‐based MRI Delta‐radiomics improve response prediction in soft‐tissue sarcomas treated by neoadjuvant chemotherapy

Evaluation of four tumour growth models to describe the natural history of meningiomas

Evaluation of four tumour growth models to describe the natural history of meningiomasResearch in context

Spatial mechanistic modeling for prediction of the growth of asymptomatic meningiomas

A Multilayer Grow-or-Go Model for GBM: Effects of Invasive Cells and Anti-Angiogenesis on Growth

Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19

Abstract B2-18: Mechanisms of GBM progression on bevacizumab: Model predictions

Computational Modeling of Solid Tumor Growth: The Avascular Stage

Spatial mechanistic modeling for prediction of the growth of asymptomatic meningioma

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