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Andrea Hawkins-Daarud
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2020 – today
- 2024
- [j4]Hairong Wang, Michael G. Argenziano, Hyunsoo Yoon
, Deborah Boyett, Akshay Save, Petros Petridis
Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma. npj Digit. Medicine 7(1) (2024) - [j3]Lingchao Mao
Weakly-Supervised Transfer Learning With Application in Precision Medicine. IEEE Trans Autom. Sci. Eng. 21(4): 6250-6264 (2024) - [i1]Lujia Wang, 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, Devi P. Patra, Bernard R. Bendok, Kris A. Smith, Peter Nakaji, Kliment Donev, Leslie C. Baxter, Maciej M. Mrugala, Michele Ceccarelli, Antonio Iavarone, Kristin R. Swanson, Nhan L. Tran, Leland S. Hu, Jing Li:
Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. CoRR abs/2401.00128 (2024) - 2022
- [j2]Lujia Wang
Knowledge-Infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine. IEEE Trans Autom. Sci. Eng. 19(3): 2203-2215 (2022) - 2020
- [j1]Jill Gallaher
From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response. PLoS Comput. Biol. 16(2) (2020) - [c3]Pamela R. Jackson
Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth. SASHIMI@MICCAI 2020: 32-40
2010 – 2019
- 2019
- [c2]Sara Ranjbar
Sex Differences in Predicting Fluid Intelligence of Adolescent Brain from T1-Weighted MRIs. ABCD-NP@MICCAI 2019: 150-157 - 2018
- [c1]Pamela R. Jackson
Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment. Image Perception, Observer Performance, and Technology Assessment 2018: 105771D
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