Zobrazeno 1 - 10
of 354
pro vyhledávání: '"Hawkins-Daarud A"'
Autor:
Wang, Lujia, Wang, Hairong, D'Angelo, Fulvio, Curtin, Lee, Sereduk, Christopher P., De Leon, Gustavo, Singleton, Kyle W., Urcuyo, Javier, Hawkins-Daarud, Andrea, Jackson, Pamela R., Krishna, Chandan, Zimmerman, Richard S., Patra, Devi P., Bendok, Bernard R., Smith, Kris A., Nakaji, Peter, Donev, Kliment, Baxter, Leslie C., Mrugała, Maciej M., Ceccarelli, Michele, Iavarone, Antonio, Swanson, Kristin R., Tran, Nhan L., Hu, Leland S., Li, Jing
Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learnin
Externí odkaz:
http://arxiv.org/abs/2401.00128
Autor:
Hairong Wang, Michael G. Argenziano, Hyunsoo Yoon, Deborah Boyett, Akshay Save, Petros Petridis, William Savage, Pamela Jackson, Andrea Hawkins-Daarud, Nhan Tran, Leland Hu, Kyle W. Singleton, Lisa Paulson, Osama Al Dalahmah, Jeffrey N. Bruce, Jack Grinband, Kristin R. Swanson, Peter Canoll, Jing Li
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-14 (2024)
Abstract Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of recurrent glioblastoma. This study addresses the need for non-invasive approaches to map heterogeneous landscape of histopathological alterations thro
Externí odkaz:
https://doaj.org/article/d5dad2992549480bb73b3faa28c1de97
Autor:
Leland S. Hu, Fulvio D’Angelo, Taylor M. Weiskittel, Francesca P. Caruso, Shannon P. Fortin Ensign, Mylan R. Blomquist, Matthew J. Flick, Lujia Wang, Christopher P. Sereduk, Kevin Meng-Lin, Gustavo De Leon, Ashley Nespodzany, Javier C. Urcuyo, Ashlyn C Gonzales, Lee Curtin, Erika M. Lewis, Kyle W. Singleton, Timothy Dondlinger, Aliya Anil, Natenael B. Semmineh, Teresa Noviello, Reyna A. Patel, Panwen Wang, Junwen Wang, Jennifer M. Eschbacher, Andrea Hawkins-Daarud, Pamela R. Jackson, Itamar S. Grunfeld, Christian Elrod, Gina L. Mazza, Sam C. McGee, Lisa Paulson, Kamala Clark-Swanson, Yvette Lassiter-Morris, Kris A. Smith, Peter Nakaji, Bernard R. Bendok, Richard S. Zimmerman, Chandan Krishna, Devi P. Patra, Naresh P. Patel, Mark Lyons, Matthew Neal, Kliment Donev, Maciej M. Mrugala, Alyx B. Porter, Scott C. Beeman, Todd R. Jensen, Kathleen M. Schmainda, Yuxiang Zhou, Leslie C. Baxter, Christopher L. Plaisier, Jing Li, Hu Li, Anna Lasorella, C. Chad Quarles, Kristin R. Swanson, Michele Ceccarelli, Antonio Iavarone, Nhan L. Tran
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-20 (2023)
Abstract Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular
Externí odkaz:
https://doaj.org/article/a2809ec273b7446289807a553cea6a7f
Autor:
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 Mrugała, Michele Ceccarelli, Antonio Iavarone, Kristin R Swanson, Nhan L Tran, Leland S Hu, Jing Li
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0299267 (2024)
Background and objectiveGlioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, M
Externí odkaz:
https://doaj.org/article/b57d4faef51a40fca14cffc4c306cabd
Autor:
Nardini, John T., Lagergren, John H., Hawkins-Daarud, Andrea, Curtin, Lee, Morris, Bethan, Rutter, Erica M., Swanson, Kristin R., Flores, Kevin B.
Equation learning methods present a promising tool to aid scientists in the modeling process for biological data. Previous equation learning studies have demonstrated that these methods can infer models from rich datasets, however, the performance of
Externí odkaz:
http://arxiv.org/abs/2005.09622
Akademický článek
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Autor:
Ranjbar, Sara, Singleton, Kyle W., Curtin, Lee, Massey, Susan Christine, Hawkins-Daarud, Andrea, Jackson, Pamela R., Swanson, Kristin R.
Fluid intelligence (Gf) has been defined as the ability to reason and solve previously unseen problems. Links to Gf have been found in magnetic resonance imaging (MRI) sequences such as functional MRI and diffusion tensor imaging. As part of the Adol
Externí odkaz:
http://arxiv.org/abs/1908.02333
Autor:
Javier C Urcuyo, Lee Curtin, Jazlynn M Langworthy, Gustavo De Leon, Barrett Anderies, Kyle W Singleton, Andrea Hawkins-Daarud, Pamela R Jackson, Kamila M Bond, Sara Ranjbar, Yvette Lassiter-Morris, Kamala R Clark-Swanson, Lisa E Paulson, Chris Sereduk, Maciej M Mrugala, Alyx B Porter, Leslie Baxter, Marcela Salomao, Kliment Donev, Miles Hudson, Jenna Meyer, Qazi Zeeshan, Mithun Sattur, Devi P Patra, Breck A Jones, Rudy J Rahme, Matthew T Neal, Naresh Patel, Pelagia Kouloumberis, Ali H Turkmani, Mark Lyons, Chandan Krishna, Richard S Zimmerman, Bernard R Bendok, Nhan L Tran, Leland S Hu, Kristin R Swanson
Publikováno v:
PLoS ONE, Vol 18, Iss 12, p e0287767 (2023)
Brain cancers pose a novel set of difficulties due to the limited accessibility of human brain tumor tissue. For this reason, clinical decision-making relies heavily on MR imaging interpretation, yet the mapping between MRI features and underlying bi
Externí odkaz:
https://doaj.org/article/9e0a2b9676eb4c9582d28ead00177ffa
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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K zobrazení výsledku je třeba se přihlásit.
Autor:
Mao, Lingchao, Wang, Lujia, Hu, Leland S., Eschbacher, Jenny M., Leon, Gustavo De, Singleton, Kyle W., Curtin, Lee A., Urcuyo, Javier, Sereduk, Chris, Tran, Nhan L., Hawkins-Daarud, Andrea, Swanson, Kristin R., Li, Jing
Publikováno v:
IEEE Transactions on Automation Science and Engineering: A Publication of the IEEE Robotics and Automation Society; October 2024, Vol. 21 Issue: 4 p6250-6264, 15p