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ORCIDPRNI 2018: Singapore
- 2018 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2018, Singapore, Singapore, June 12-14, 2018. IEEE 2018, ISBN 978-1-5386-6859-7
- Jessica Schrouff, Janaina Mourão Miranda:
Interpreting weight maps in terms of cognitive or clinical neuroscience: nonsense? 1-4 - Amicie de Pierrefeu, Tommy Löfstedt, Charles Laidi, Fouad Hadj-Selem
, Marion Leboyer, Philippe Ciuciu, Josselin Houenou, Edouard Duchesnay:
Interpretable and stable prediction of schizophrenia on a large multisite dataset using machine learning with structured sparsity. 1-4 - Fabio S. Ferreira, Maria João Duarte Rosa, Michael Moutoussis, Ray Dolan, John Shawe-Taylor, John Ashburner, Janaina Mourão Miranda:
Sparse PLS hyper-parameters optimisation for investigating brain-behaviour relationships. 1-4 - Irene Fantini, Letícia Rittner, Clarissa L. Yasuda, Roberto A. Lotufo:
Automatic detection of motion artifacts on MRI using Deep CNN. 1-4 - Evangelos Sigalas, Junhua Li, Anastasios Bezerianos, Chris G. Antonopoulos:
Emergence of Chimera-like States in Prefrontal-Cortex Macaque Intracranial Recordings. 1-4 - Yaelan Jung, Bart Larsen, Dirk B. Walther:
Using decoding error patterns to trace the neural signature of auditory scene perception. 1-4 - Jiancong He, Guoxu Zhou, Hongtao Wang, Evangelos Sigalas, Nitish V. Thakor, Anastasios Bezerianos, Junhua Li:
Boosting Transfer Learning Improves Performance of Driving Drowsiness Classification Using EEG. 1-4 - Qi Wang, Ievgen Redko, Sylvain Takerkart:
Population Averaging of Neuroimaging Data Using Lp Distance-based Optimal Transport. 1-4 - Brian Murphy, Andrea Aleni, Brahim Belaoucha, John Dyer, Hugh Nolan:
Quantifying cognitive aging and performance with at-home gamified mobile EEG. 1-4 - Minh Nguyen, Nanbo Sun, Daniel C. Alexander, Jiashi Feng, B. T. Thomas Yeo:
Modeling Alzheimer's disease progression using deep recurrent neural networks. 1-4 - Stanislas Chambon, Mathieu N. Galtier, Alexandre Gramfort:
Domain adaptation with optimal transport improves EEG sleep stage classifiers. 1-4 - Tong He, Ru Kong, Avram J. Holmes, Mert R. Sabuncu, Simon B. Eickhoff, Danilo Bzdok, Jiashi Feng, B. T. Thomas Yeo:
Is deep learning better than kernel regression for functional connectivity prediction of fluid intelligence? 1-4 - Fermín Segovia, Juan Manuel Górriz, Javier Ramírez, Francisco Jesús Martínez-Murcia, Diego Castillo-Barnes, R. Sanchez-Vano, Pablo Sopena-Novales, Manuel Gómez-Río:
Using Early Acquisitions of Amyloid-PET as a Surrogate of FDG-PET: A Machine Learning Based Approach. 1-4 - Ricardo P. M. Cruz, Margarida Silveira, Jaime S. Cardoso:
A Class Imbalance Ordinal Method for Alzheimer's Disease Classification. 1-4 - Darya Chyzhyk, Gaël Varoquaux, Bertrand Thirion, Michael P. Milham:
Controlling a confound in predictive models with a test set minimizing its effect. 1-4 - Martin Nørgaard, Douglas N. Greve, Claus Svarer, Stephen C. Strother, Gitte Moos Knudsen, Melanie Ganz:
The Impact of Preprocessing Pipeline Choice in Univariate and Multivariate Analyses of PET Data. 1-4 - Valeria Kebets, Mitsouko van Assche, Jonas Richiardi, Rachel Goldstein, Reto Meuli, Tobias Kober, Frédéric Assal, Dimitri Van De Ville:
Multivariate and predictive modelling of neural variability in mild cognitive impairment. 1-4 - Hanh Vu, Hyun-Chul Kim, Jong-Hwan Lee:
3D convolutional neural network for feature extraction and classification of fMRI volumes. 1-4 - Robyn L. Miller, Vince D. Calhoun:
Dynamic Whole Brain Polarity Regimes Strongly Distinguish Controls from Schizophrenia Patients. 1-4 - Søren Føns Vind Nielsen, Diego Vidaurre, Kristoffer Hougaard Madsen, Mikkel N. Schmidt, Morten Mørup:
Testing group differences in state transition structure of dynamic functional connectivity models. 1-4
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