Zobrazeno 21 - 30
of 3 993
pro vyhledávání: '"Thompson, Paul P."'
Autor:
Tang, Haoteng, Fu, Xiyao, Guo, Lei, Wang, Yalin, Mackin, Scott, Ajilore, Olusola, Leow, Alex, Thompson, Paul, Huang, Heng, Zhan, Liang
MRI-based modeling of brain networks has been widely used to understand functional and structural interactions and connections among brain regions, and factors that affect them, such as brain development and disease. Graph mining on brain networks ma
Externí odkaz:
http://arxiv.org/abs/2205.07854
Autor:
Wu, Jianfeng, Zhu, Wenhui, Su, Yi, Gui, Jie, Lepore, Natasha, Reiman, Eric M., Caselli, Richard J., Thompson, Paul M., Chen, Kewei, Wang, Yalin
Biomarker-assisted diagnosis and intervention in Alzheimer's disease (AD) may be the key to prevention breakthroughs. One of the hallmarks of AD is the accumulation of tau plaques in the human brain. However, current methods to detect tau pathology a
Externí odkaz:
http://arxiv.org/abs/2110.10709
Autor:
Stripelis, Dimitris, Saleem, Hamza, Ghai, Tanmay, Dhinagar, Nikhil, Gupta, Umang, Anastasiou, Chrysovalantis, Steeg, Greg Ver, Ravi, Srivatsan, Naveed, Muhammad, Thompson, Paul M., Ambite, Jose Luis
Federated learning (FL) enables distributed computation of machine learning models over various disparate, remote data sources, without requiring to transfer any individual data to a centralized location. This results in an improved generalizability
Externí odkaz:
http://arxiv.org/abs/2108.03437
Autor:
Gupta, Umang, Stripelis, Dimitris, Lam, Pradeep K., Thompson, Paul M., Ambite, José Luis, Steeg, Greg Ver
Ensuring the privacy of research participants is vital, even more so in healthcare environments. Deep learning approaches to neuroimaging require large datasets, and this often necessitates sharing data between multiple sites, which is antithetical t
Externí odkaz:
http://arxiv.org/abs/2105.02866
Semantic search engines, which integrate the output of text mining (TM) methods, can significantly increase the ease and efficiency of finding relevant documents and locating important information within them. We present a novel search engine for the
Externí odkaz:
http://arxiv.org/abs/2103.12420
The amount of biomedical data continues to grow rapidly. However, the ability to analyze these data is limited due to privacy and regulatory concerns. Machine learning approaches that require data to be copied to a single location are hampered by the
Externí odkaz:
http://arxiv.org/abs/2102.08440
Deep Learning for neuroimaging data is a promising but challenging direction. The high dimensionality of 3D MRI scans makes this endeavor compute and data-intensive. Most conventional 3D neuroimaging methods use 3D-CNN-based architectures with a larg
Externí odkaz:
http://arxiv.org/abs/2102.04438
We propose an interpretable 3D Grid-Attention deep neural network that can accurately predict a person's age and whether they have Alzheimer's disease (AD) from a structural brain MRI scan. Building on a 3D convolutional neural network, we added two
Externí odkaz:
http://arxiv.org/abs/2011.09115
Autor:
Geprägs, Stephan, Skovdal, Björn Erik, Scheufele, Monika, Opel, Matthias, Wermeille, Didier, Thompson, Paul, Bombardi, Alessandro, Simonet, Virginie, Grenier, Stéphane, Lejay, Pascal, Chahine, Gilbert Andre, Castro, Diana Quintero, Gross, Rudolf, Mannix, Dan
We report on a comprehensive investigation of the effects of strain and film thickness on the structural and magnetic properties of epitaxial thin films of the prototypal $J_\mathrm{eff}=1/2$ compound Sr$_2$IrO$_4$ by advanced X-ray scattering. We fi
Externí odkaz:
http://arxiv.org/abs/2009.13185
Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology, for an individual brain, mining a discriminative network representat
Externí odkaz:
http://arxiv.org/abs/2007.09777