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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.1135-1143

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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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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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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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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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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Machine Learning and Mechanistic Modeling for Prediction of Metastatic Relapse in Early-Stage Breast Cancer

JCO clinical cancer informatics, 2020-03 (4), p.259-274

2020

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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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Spatial mechanistic modeling for prediction of the growth of asymptomatic meningioma

Computer methods and programs in biomedicine, 2020

2020

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TMOD−03 Motility controls growth and progression patterns of glioblastoma multiforme

Neuro-oncology (Charlottesville, Va.), 2015-11

2015

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TMOD-03MOTILITY CONTROLS GROWTH AND PROGRESSION PATTERNS OF GLIOBLASTOMA MULTIFORME

Neuro-oncology (Charlottesville, Va.), 2015-11, Vol.17 (suppl 5), p.v226.3-v226

2015

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Comparison of MRI-based response criteria and radiomics for the prediction of early response to transarterial radioembolization in patients with hepatocellular carcinoma

Diagnostic and interventional imaging, 2022-07, Vol.103 (7-8), p.360-366

2022

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Spatial modelling of tumour drug resistance: the case of GIST liver metastases

IMA journal of management mathematics, 2017-06, Vol.34 (2), p.151-176

2017

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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

Computational Modelling of Metastasis Development in Renal Cell Carcinoma

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?

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

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

Computational Modeling of Solid Tumor Growth: The Avascular Stage

Machine Learning and Mechanistic Modeling for Prediction of Metastatic Relapse in Early-Stage Breast Cancer

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

Spatial mechanistic modeling for prediction of the growth of asymptomatic meningioma

TMOD−03 Motility controls growth and progression patterns of glioblastoma multiforme

TMOD-03MOTILITY CONTROLS GROWTH AND PROGRESSION PATTERNS OF GLIOBLASTOMA MULTIFORME

Comparison of MRI-based response criteria and radiomics for the prediction of early response to transarterial radioembolization in patients with hepatocellular carcinoma

Spatial modelling of tumour drug resistance: the case of GIST liver metastases

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