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pro vyhledávání: '"Ngo, Gia H."'
Given sufficient pairs of resting-state and task-evoked fMRI scans from subjects, it is possible to train ML models to predict subject-specific task-evoked activity using resting-state functional MRI (rsfMRI) scans. However, while rsfMRI scans are re
Externí odkaz:
http://arxiv.org/abs/2310.14105
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2024)
The Granger framework is useful for discovering causal relations in time-varying signals. However, most Granger causality (GC) methods are developed for densely sampled timeseries data. A substantially different setting, particularly common in medica
Externí odkaz:
http://arxiv.org/abs/2210.07416
Publikováno v:
Medical Image Analysis. 2022 Jul 19:102540
Neuroimaging studies are often limited by the number of subjects and cognitive processes that can be feasibly interrogated. However, a rapidly growing number of neuroscientific studies have collectively accumulated an extensive wealth of results. Dig
Externí odkaz:
http://arxiv.org/abs/2208.00840
Most neuroimaging experiments are under-powered, limited by the number of subjects and cognitive processes that an individual study can investigate. Nonetheless, over decades of research, neuroscience has accumulated an extensive wealth of results. I
Externí odkaz:
http://arxiv.org/abs/2109.13814
Visual perception is critically influenced by the focus of attention. Due to limited resources, it is well known that neural representations are biased in favor of attended locations. Using concurrent eye-tracking and functional Magnetic Resonance Im
Externí odkaz:
http://arxiv.org/abs/2010.00516
Spell check is a useful application which processes noisy human-generated text. Spell check for Chinese poses unresolved problems due to the large number of characters, the sparse distribution of errors, and the dearth of resources with sufficient co
Externí odkaz:
http://arxiv.org/abs/2008.12281
Resting-state functional MRI (rsfMRI) yields functional connectomes that can serve as cognitive fingerprints of individuals. Connectomic fingerprints have proven useful in many machine learning tasks, such as predicting subject-specific behavioral tr
Externí odkaz:
http://arxiv.org/abs/2008.02961
The increasing popularity of naturalistic paradigms in fMRI (such as movie watching) demands novel strategies for multi-subject data analysis, such as use of neural encoding models. In the present study, we propose a shared convolutional neural encod
Externí odkaz:
http://arxiv.org/abs/2006.15802
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 28, pp. 461-473, 2020
Logographs (Chinese characters) have recursive structures (i.e. hierarchies of sub-units in logographs) that contain phonological and semantic information, as developmental psychology literature suggests that native speakers leverage on the structure
Externí odkaz:
http://arxiv.org/abs/1912.09913
Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI. W
Externí odkaz:
http://arxiv.org/abs/1812.11477