Kristin Swanson
0000-0002-2464-6119
51 papers found
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Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies
The 2019 mathematical oncology roadmap
Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning
Quantifying Uncertainty and Robustness in a Biomathematical Model Based Patient-Specific Response Metric for Glioblastoma
Hybrid approach for parameter estimation in agent-based models
The role of IDH1 mutated tumour cells in secondary glioblastomas: an evolutionary game theoretical view
Magnetic Resonance Imaging Characteristics of Glioblastoma Multiforme: Implications for Understanding Glioma Ontogeny
Predicting the efficacy of radiotherapy in individual glioblastoma patientsin vivo:a mathematical modeling approach
Pdgf-Driven Glioma Model Reveals That Environmentally Targeted Therapies May Be More Effective at Altering Recurrent Disease Kinetics
Predicting Spatial Patterns of Tumor Recurrence Following Radiation Therapy: A Hybrid Clinical Imaging and Mathematical Modeling Approach
Ellsworth "Buster" Alvord (1923-2010) OBITUARY
Pre-Treatment Glioblastoma Proliferation and Invasion Kinetics: A Mechanism to Predict Pseudoprogression
Direct Inhibition of Non-Muscle Myosin Ii Effectively Blocks Glioma Invasion in the Presence of Multiple Motogens
In Silico Pet Imaging: From Anatomic Glioma Growth Dynamics to Metabolic Tumor Activity via Bio-Mathematical Modeling
Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model
Quantitative metrics of net proliferation and invasion link biological aggressiveness assessed by MRI with hypoxia assessed by FMISO-PET in newly diagnosed glioblastomas
Opportunities for Personalized Treatment and Management of Malignant Gliomas: The Clinical Significance of Mathematical Models
Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastoma: A Role for Patient-Specific Virtual Controls
Modeling the Effects of Progenitor Cell Recruitment on Glioma Growth and Progression
Patient-Specific Virtual Controls Can Be Used to Simulate and Predict Response to Radiation Therapy in Individual Glioblastoma Patients
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