Zobrazeno 1 - 10
of 517
pro vyhledávání: '"Jean-Pierre R"'
Autor:
Jean-Pierre R. Falet, Joshua Durso-Finley, Brennan Nichyporuk, Julien Schroeter, Francesca Bovis, Maria-Pia Sormani, Doina Precup, Tal Arbel, Douglas Lorne Arnold
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-12 (2022)
There are limited predictive biomarkers for drug treatment responses in individuals with multiple sclerosis. Here using existing clinical trials data, the authors propose a deep-learning predictive enrichment strategy to identify which participants a
Externí odkaz:
https://doaj.org/article/eebb56feac2e443f8d353be6ee0c9d86
Autor:
Jean-Pierre R. Falet, Jonathan Côté, Veronica Tarka, Zaida Escila Martínez-Moreno, Patrice Voss, Etienne de Villers-Sidani
Publikováno v:
NeuroImage, Vol 238, Iss , Pp 118222- (2021)
We present a novel method to map the functional organization of the human auditory cortex noninvasively using magnetoencephalography (MEG). More specifically, this method estimates via reverse correlation the spectrotemporal receptive fields (STRF) i
Externí odkaz:
https://doaj.org/article/8b3970778617454487049b90b4777288
Autor:
Kumar, Amar, Fathi, Nima, Mehta, Raghav, Nichyporuk, Brennan, Falet, Jean-Pierre R., Tsaftaris, Sotirios, Arbel, Tal
Deep learning models can perform well in complex medical imaging classification tasks, even when basing their conclusions on spurious correlations (i.e. confounders), should they be prevalent in the training dataset, rather than on the causal image m
Externí odkaz:
http://arxiv.org/abs/2308.10984
Autor:
Hu, Anjun, Falet, Jean-Pierre R., Nichyporuk, Brennan S., Shui, Changjian, Arnold, Douglas L., Tsaftaris, Sotirios A., Arbel, Tal
We propose a hierarchically structured variational inference model for accurately disentangling observable evidence of disease (e.g. brain lesions or atrophy) from subject-specific anatomy in brain MRIs. With flexible, partially autoregressive priors
Externí odkaz:
http://arxiv.org/abs/2211.07820
Autor:
Nichyporuk, Brennan, Cardinell, Jillian, Szeto, Justin, Mehta, Raghav, Falet, Jean-Pierre R., Arnold, Douglas L., Tsaftaris, Sotirios A., Arbel, Tal
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 1 (2022)
Generalization is an important attribute of machine learning models, particularly for those that are to be deployed in a medical context, where unreliable predictions can have real world consequences. While the failure of models to generalize across
Externí odkaz:
http://arxiv.org/abs/2210.17398
Autor:
Kumar, Amar, Hu, Anjun, Nichyporuk, Brennan, Falet, Jean-Pierre R., Arnold, Douglas L., Tsaftaris, Sotirios, Arbel, Tal
The discovery of patient-specific imaging markers that are predictive of future disease outcomes can help us better understand individual-level heterogeneity of disease evolution. In fact, deep learning models that can provide data-driven personalize
Externí odkaz:
http://arxiv.org/abs/2208.02311
Autor:
Durso-Finley, Joshua, Falet, Jean-Pierre R., Nichyporuk, Brennan, Arnold, Douglas L., Arbel, Tal
Precision medicine for chronic diseases such as multiple sclerosis (MS) involves choosing a treatment which best balances efficacy and side effects/preferences for individual patients. Making this choice as early as possible is important, as delays i
Externí odkaz:
http://arxiv.org/abs/2204.01702
Autor:
Falet, Jean-Pierre R., Côté, Jonathan, Tarka, Veronica, Martínez-Moreno, Zaida Escila, Voss, Patrice, de Villers-Sidani, Etienne
Publikováno v:
In NeuroImage September 2021 238
Autor:
Trott, Cathryn M., Tingay, Steven J., Wayth, Randall B., Thompson, David R., Deller, Adam T., Brisken, Walter F., Wagstaff, Kiri L., Majid, Walid A., Burke-Spolaor, Sarah, Macquart, Jean-Pierre R., Palaniswamy, Divya
We define a framework for determining constraints on the detection rate of fast transient events from a population of underlying sources, with a view to incorporating beam shape, frequency effects, scattering effects, and detection efficiency into th
Externí odkaz:
http://arxiv.org/abs/1301.5951
Transient radio signals of astrophysical origin present an avenue for studying the dynamic universe. With the next generation of radio interferometers being planned and built, there is great potential for detecting and studying large samples of radio
Externí odkaz:
http://arxiv.org/abs/1102.3746