Kristin R. Swanson

发表

NIMG-17. UTILIZING MACHINE LEARNING FOR PREDICTIVE MODELING OF SEIZURE PRESENTATION IN GLIOMA PATIENTS.

Leland S. Hu, Aditya Khurana, Sara Ranjbar, 2018 .

Quantifying glioma cell growth and invasion in vitro

Kristin R. Swanson, K. Swanson, 2008, Math. Comput. Model..

NIMG-52. UNCERTAINTY QUANTIFICATION IN RADIOMICS

Hyunsoo Yoon, Lujia Wang, Teresa Wu, 2019 .

From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response

Alexander R. A. Anderson, Sandra K. Johnston, Kristin R. Swanson, 2019, bioRxiv.

NIMG-30. REPRODUCIBLE RADIOMIC MAPPING OF TUMOR CELL DENSITY BY MACHINE LEARNING AND DOMAIN ADAPTATION

Hyunsoo Yoon, Lujia Wang, Teresa Wu, 2019 .

A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type

Leland S. Hu, Kristin R. Swanson, Sara Ranjbar, 2019, Journal of Digital Imaging.

Connecting MRI Physics to Glioma Microenvironment: Comparing Simulated T2-Weighted MRI Models of Fixed and Expanding Extracellular Space

Kristin R. Swanson, Andrea Hawkins-Daarud, Kamala Clark-Swanson, 2017 .

Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet pdf

Leland S. Hu, Kristin R. Swanson, Sara Ranjbar, 2020, ArXiv.

MetaMarker: a pipeline for de novo discovery of novel metagenomic biomarkers

Junwen Wang, Kristin R. Swanson, Nhan L. Tran, 2019, Bioinform..

Sex Differences in Predicting Fluid Intelligence of Adolescent Brain from T1-Weighted MRIs

Kristin R. Swanson, Andrea Hawkins-Daarud, Susan Christine Massey, 2019, ABCD-NP@MICCAI.

Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth

Kristin R. Swanson, Pamela R. Jackson, Andrea Hawkins-Daarud, 2020, SASHIMI@MICCAI.

Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment

Kristin R. Swanson, Paul E. Kinahan, Andrea Hawkins-Daarud, 2018, Medical Imaging.

Quantifying Uncertainty and Robustness in a Biomathematical Model Based Patient-Specific Response Metric for Glioblastoma

Sandra K. Johnston, Kristin R. Swanson, Andrea Hawkins-Daarud, 2018, bioRxiv.

Hybrid approach for parameter estimation in agent-based models

Alexander R. A. Anderson, Kristin R. Swanson, Andrea Hawkins-Daarud, 2017, bioRxiv.

A digital reference object for the 3D Hoffman brain phantom for characterization of PET neuroimaging quality

Mark Muzi, Sandra K. Johnston, Kristin R. Swanson, 2013, 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC).

Bridging from multiscale modeling to practical clinical applications in the study of human gliomas

Kristin R. Swanson, Gargi Chakraborty, Rita Sodt, 2010 .

Knowledge-Infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine

Leland S. Hu, Kristin R. Swanson, Andrea Hawkins-Daarud, 2021, IEEE Transactions on Automation Science and Engineering.

Patient-Specific Metrics of Invasiveness Reveal Significant Prognostic Benefit of Resection in a Predictable Subset of Gliomas

Kristin R. Swanson, Guy M. McKhann, Albert Lai, 2014, PloS one.

Toward Patient-Specific, Biologically Optimized Radiation Therapy Plans for the Treatment of Glioblastoma

Kristin R. Swanson, Russell C. Rockne, Robert D. Stewart, 2013, PloS one.

Complementary but Distinct Roles for MRI and 18F-Fluoromisonidazole PET in the Assessment of Human Glioblastomas

Kristin R. Swanson, Gargi Chakraborty, Mark Muzi, 2008, Journal of Nuclear Medicine.

Dynamics of a model for brain tumors reveals a small window for therapeutic intervention

Kristin R. Swanson, James D. Murray, Ellsworth C. Alvord, 2003 .

Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric

Kristin R. Swanson, Maxwell Lewis Neal, Russell C. Rockne, 2013, PloS one.

Patient-Specific Mathematical Neuro-Oncology: Using a Simple Proliferation and Invasion Tumor Model to Inform Clinical Practice

Kristin R. Swanson, Andrea Hawkins-Daarud, Russell C. Rockne, 2015, Bulletin of mathematical biology.

Defining Glioblastoma Resectability Through the Wisdom of the Crowd: A Proof-of-Principle Study

David W. Roberts, Oren Sagher, Theodore H. Schwartz, 2016, Neurosurgery.

Virtual resection of gliomas: Effect of extent of resection on recurrence

Kristin R. Swanson, James D. Murray, Ellsworth C. Alvord, 2003 .

Quantifying Uncertainty and Robustness in a Biomathematical Model–Based Patient-Specific Response Metric for Glioblastoma

Sandra K. Johnston, Kristin R. Swanson, Andrea Hawkins-Daarud, 2019, JCO clinical cancer informatics.

Response classification based on a minimal model of glioblastoma growth is prognostic for clinical outcomes and distinguishes progression from pseudoprogression.

Kristin R. Swanson, Maxwell Lewis Neal, Russell C. Rockne, 2013, Cancer research.

The Evolution of Mathematical Modeling of Glioma Proliferation and Invasion

Kristin R. Swanson, Ellsworth C. Alvord, K. Swanson, 2007, Journal of neuropathology and experimental neurology.

Modeling Diffusely Invading Brain Tumors An Individualized Approach to Quantifying Glioma Evolution and Response to Therapy

Kristin R. Swanson, Gargi Chakraborty, Stanley Gu, 2008 .