Quantifying glioma cell growth and invasion in vitro. - Kristin R. Swanson (Math. Comput. Model., 2008)

Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment. - Pamela R. Jackson; Andrea Hawkins-Daarud; Savannah C. Partridge; Paul E. Kinahan; Kristin R. Swanson (Image Perception, Observer Performance, and Technology Assessment, 2018)

Sex Differences in Predicting Fluid Intelligence of Adolescent Brain from T1-Weighted MRIs. - Sara Ranjbar; Kyle W. Singleton; Lee Curtin; Susan Christine Massey; Andrea Hawkins-Daarud; Pamela R. Jackson; Kristin R. Swanson (ABCD-NP@MICCAI, 2019)

MetaMarker: a pipeline for de novo discovery of novel metagenomic biomarkers. - Mohamad Koohi-Moghadam; Mitesh J. Borad; Nhan L. Tran; Kristin R. Swanson; Lisa Boardman; Hong-Zhe Su; Junwen Wang (Bioinform., 2019)

Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth. - Pamela R. Jackson; Andrea Hawkins-Daarud; Kristin R. Swanson (SASHIMI@MICCAI, 2020)

Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet. - Sara Ranjbar; Kyle W. Singleton; Lee Curtin; Cassandra R. Rickertsen; Lisa E. Paulson; Leland S. Hu; Joseph Ross Mitchell; Kristin R. Swanson (CoRR, 2020)

A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type. - Sara Ranjbar; Kyle W. Singleton; Pamela R. Jackson; Cassandra R. Rickertsen; Scott A. Whitmire; Kamala R. Clark-Swanson; Joseph Ross Mitchell; Kristin R. Swanson; Leland S. Hu (J. Digit. Imaging, 2020)

From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response. - Jill Gallaher; Susan Christine Massey; Andrea Hawkins-Daarud; Sonal S. Noticewala; Russell C. Rockne; Sandra K. Johnston; Luis Gonzalez-Cuyar; Joseph Juliano; Orlando Gil; Kristin R. Swanson; Peter D. Canoll; Alexander R. A. Anderson (PLoS Comput. Biol., 2020)

Knowledge-Infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine. - Lujia Wang 002; Andrea Hawkins-Daarud; Kristin R. Swanson; Leland S. Hu; Jing Li 016 (IEEE Trans Autom. Sci. Eng., 2022)

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. - Lujia Wang 002; Hairong Wang; Fulvio D'Angelo; Lee Curtin; Christopher P. Sereduk; Gustavo De Leon; Kyle W. Singleton; Javier Urcuyo; Andrea Hawkins-Daarud; Pamela R. Jackson; Chandan Krishna; Richard S. Zimmerman; et al. (CoRR, 2024)

Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma. - Hairong Wang; Michael G. Argenziano; Hyunsoo Yoon; Deborah Boyett; Akshay Save; Petros Petridis; William Savage; Pamela R. Jackson; Andrea Hawkins-Daarud; Nhan L. Tran; Leland S. Hu; Kyle W. Singleton; et al. (npj Digit. Medicine, 2024)

Weakly-Supervised Transfer Learning With Application in Precision Medicine. - Lingchao Mao; Lujia Wang 002; Leland S. Hu; Jenny M. Eschbacher; Gustavo De Leon; Kyle W. Singleton; Lee Curtin; Javier Urcuyo; Christopher P. Sereduk; Nhan L. Tran; Andrea Hawkins-Daarud; Kristin R. Swanson; et al. (IEEE Trans Autom. Sci. Eng., 2024)

Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A Review. - Lingchao Mao; Hairong Wang; Leland S. Hu; Nhan L. Tran; Peter D. Canoll; Kristin R. Swanson; Jing Li 016 (IEEE Trans Autom. Sci. Eng., 2025)