Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Jane M. Rondina"'
Publikováno v:
NeuroImage: Clinical, Vol 12, Iss C, Pp 372-380 (2016)
Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine
Externí odkaz:
https://doaj.org/article/6950a31c42dc40e4b53acff956cb44d5
Autor:
Luiz K. Ferreira, Jane M. Rondina, Rodrigo Kubo, Carla R. Ono, Claudia C. Leite, Jerusa Smid, Cassio Bottino, Ricardo Nitrini, Geraldo F. Busatto, Fabio L. Duran, Carlos A. Buchpiguel
Publikováno v:
Brazilian Journal of Psychiatry, Iss 0 (2017)
Objective: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flo
Externí odkaz:
https://doaj.org/article/152e5ead6b1949b4834b09f40bb8bf7e
Publikováno v:
Journal of neurology, neurosurgery, and psychiatry.
Stroke is the most common cause of neurological disability and yet our ability to predict long-term outcomes remains poor. The paper by Selles et al 1 used upper limb outcomes from 450 patients with first-time ischaemic stroke to take a refreshingly
Autor:
Jane M. Rondina, Bernadette C.M. van Wijk, Svenja Espenhahn, Nick S. Ward, Nell D. Redman, Joern Diedrichsen, Holly E. Rossiter
Publikováno v:
Brain Communications
Recovery of skilled movement after stroke is assumed to depend on motor learning. However, the capacity for motor learning and factors that influence motor learning after stroke have received little attention. In this study, we first compared motor s
Autor:
Joern Diedrichsen, Nick S. Ward, Nellie Redman, Svenja Espenhahn, Jane M. Rondina, Bernadette C.M. van Wijk, Holly E. Rossiter
Recovery of skilled movement after stroke is assumed to depend on motor learning. However, the capacity for motor learning and factors that influence motor learning after stroke have received little attention. In this study we firstly compared motor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24a9a9a9703e3eee001f7f2742947520
https://doi.org/10.1101/2020.01.15.20017665
https://doi.org/10.1101/2020.01.15.20017665
Autor:
Paul M. Thompson, Jess A. Holguin, Mohamed Salah Khlif, Nerses Sanossian, Geneviève Richard, Cathrin M. Buetefisch, Daniela Vecchio, Anup K. Bhattacharya, Nima Khoshab, Adriana Bastos Conforto, Natalia S. Rost, Bradley J. MacIntosh, Cathy M. Stinear, Andrew D. Robertson, Neda Jahanshad, Amy Brodtmann, Winston D. Byblow, Arno Villringer, Chunshui Yu, Kelene A. Fercho, Lee A. Baugh, Mark S. Shiroishi, Kristin A. Wong, Jessica M. Cassidy, Keith R. Lohse, John L. Margetis, Na Jin Seo, Darryl Hwang, Artemis Zavaliangos-Petropulu, Fabrizio Piras, Pamela Roberts, Gregory T. Thielman, Surjo R. Soekadar, George F. Wittenberg, Wai Kwong W. Tang, Sook-Lei Liew, Gianfranco Spalletta, Adrienne N. Dula, Nick S. Ward, Kathryn S Hayward, Steven C. Cramer, Lars T. Westlye, R. Cameron Craddock, Chris M. Gregory, Catherine E. Lang, Hosung Kim, Julia M. Juliano, Carolee J. Winstein, Mark R Etherton, Jane M. Rondina, Michael R. Borich, Emilio Werden, Simon Jung, Bokkyu Kim, Shahram Hadidchi, Francesca Assogna, Bavrina Bigjahan, Feroze B. Mohamed, Ander Ramos-Murguialday, Amy Kuceyeski, Elsa Ermer, Martin Lotze, Anisha Suri, Steven A. Kautz, Michael A. Dimyan, Lara A. Boyd, Nicolas Schweighofer
Publikováno v:
Human Brain Mapping
TECNALIA Publications
Fundación Tecnalia Research & Innovation
Liew, Sook-Lei; Zavaliangos-Petropulu, Artemis; Jahanshad, Neda; Lang, Catherine E; Hayward, Kathryn S; Lohse, Keith R; Juliano, Julia M; Assogna, Francesca; Baugh, Lee A; Bhattacharya, Anup K; Bigjahan, Bavrina; Borich, Michael R; Boyd, Lara A; Brodtmann, Amy; Buetefisch, Cathrin M; Byblow, Winston D; Cassidy, Jessica M; Conforto, Adriana B; Craddock, R Cameron; Dimyan, Michael A; ... (2022). The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke. Human brain mapping, 43(1), pp. 129-148. Wiley-Blackwell 10.1002/hbm.25015
Human brain mapping, vol 43, iss 1
TECNALIA Publications
Fundación Tecnalia Research & Innovation
Liew, Sook-Lei; Zavaliangos-Petropulu, Artemis; Jahanshad, Neda; Lang, Catherine E; Hayward, Kathryn S; Lohse, Keith R; Juliano, Julia M; Assogna, Francesca; Baugh, Lee A; Bhattacharya, Anup K; Bigjahan, Bavrina; Borich, Michael R; Boyd, Lara A; Brodtmann, Amy; Buetefisch, Cathrin M; Byblow, Winston D; Cassidy, Jessica M; Conforto, Adriana B; Craddock, R Cameron; Dimyan, Michael A; ... (2022). The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke. Human brain mapping, 43(1), pp. 129-148. Wiley-Blackwell 10.1002/hbm.25015
Human brain mapping, vol 43, iss 1
The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a3cd68bcf94786336033afd2c789629
Autor:
Carla Rachel Ono, Jerusa Smid, Jane M. Rondina, Luiz Kobuti Ferreira, Ricardo Nitrini, Geraldo F. Busatto, Fábio L.S. Duran, Claudia da Costa Leite, Carlos Alberto Buchpiguel, Rodrigo Kubo
Publikováno v:
NeuroImage : Clinical
NeuroImage: Clinical, Vol 17, Iss, Pp 628-641 (2018)
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
NeuroImage: Clinical, Vol 17, Iss, Pp 628-641 (2018)
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Background Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, t
Publikováno v:
Journal of Neurology, Neurosurgery, and Psychiatry
Background The ability to predict outcome after stroke is clinically important for planning treatment and for stratification in restorative clinical trials. In relation to the upper limbs, the main predictor of outcome is initial severity, with patie
Autor:
Holly E. Rossiter, Jane M. Rondina, Archy O. de Berker, Nick S. Ward, Svenja Espenhahn, Nell D. Redman, Jörn Diedrichsen, Bernadette C.M. van Wijk
Publikováno v:
Brain and Mind Institute Researchers' Publications
NeuroImage
NeuroImage, 195, 340-353. Academic Press Inc.
Neuroimage
NeuroImage
NeuroImage, 195, 340-353. Academic Press Inc.
Neuroimage
© 2019 The Authors People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1dca908a14677aace6f64ae13560d129
Autor:
Janaina Mourao-Miranda, Leticia de Oliveira, Thomas Leitner, Andreas J. Fallgatter, Jane M. Rondina, Thomas Dresler, Tim Hahn, John Shawe-Taylor, Andre F. Marquand
Publikováno v:
IEEE Transactions on Medical Imaging. 33:85-98
Feature selection (FS) methods play two important roles in the context of neuroimaging based classification: potentially increase classification accuracy by eliminating irrelevant features from the model and facilitate interpretation by identifying s