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Neuroscience and Biobehavioral Reviews
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January 15, 2017
Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications
Sandra Vieira, Walter H L Pinaya, Andrea Mechelli
Human Brain Mapping
|
October 13, 2018
Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large-scale multi-sample study
Walter H L Pinaya, Andrea Mechelli, João R Sato
Frontiers in Psychiatry
|
December 21, 2020
Brain-Age Prediction Using Shallow Machine Learning: Predictive Analytics Competition 2019
Pedro F Da Costa, Jessica Dafflon, Walter H L Pinaya
Network Neuroscience (Cambridge, Mass.)
|
July 4, 2025
A graph neural network approach to investigate brain critical states over neurodevelopment
Rodrigo M Cabral-Carvalho, Walter H L Pinaya, João R Sato
Chronic Stress (Thousand Oaks, Calif.)
|
May 23, 2020
Default Mode Network Maturation and Environmental Adversities During Childhood
Keila Rebello, Luciana M Moura, Walter H L Pinaya, et al.
Medical Image Analysis
|
May 22, 2022
Unsupervised brain imaging 3D anomaly detection and segmentation with transformers
Walter H L Pinaya, Petru-Daniel Tudosiu, Robert Gray, et al.
Network Neuroscience (Cambridge, Mass.)
|
June 30, 2021
Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach
Fernanda L Ribeiro, Felipe R C Dos Santos, João R Sato, et al.
Ebiomedicine
|
April 3, 2022
Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites
Kun Qin, Du Lei, Walter H L Pinaya, et al.
BMC Psychiatry
|
October 29, 2021
Using deep learning to classify pediatric posttraumatic stress disorder at the individual level
Jing Yang, Du Lei, Kun Qin, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
June 30, 2025
Simulating dynamic tumor contrast enhancement in breast MRI using conditional generative adversarial networks
Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 29) with videos related to
Sort By:
Page
of 3
Neuroscience and Biobehavioral Reviews
|
January 15, 2017
Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications
Sandra Vieira, Walter H L Pinaya, Andrea Mechelli
Human Brain Mapping
|
October 13, 2018
Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large-scale multi-sample study
Walter H L Pinaya, Andrea Mechelli, João R Sato
Frontiers in Psychiatry
|
December 21, 2020
Brain-Age Prediction Using Shallow Machine Learning: Predictive Analytics Competition 2019
Pedro F Da Costa, Jessica Dafflon, Walter H L Pinaya
Network Neuroscience (Cambridge, Mass.)
|
July 4, 2025
A graph neural network approach to investigate brain critical states over neurodevelopment
Rodrigo M Cabral-Carvalho, Walter H L Pinaya, João R Sato
Chronic Stress (Thousand Oaks, Calif.)
|
May 23, 2020
Default Mode Network Maturation and Environmental Adversities During Childhood
Keila Rebello, Luciana M Moura, Walter H L Pinaya, et al.
Medical Image Analysis
|
May 22, 2022
Unsupervised brain imaging 3D anomaly detection and segmentation with transformers
Walter H L Pinaya, Petru-Daniel Tudosiu, Robert Gray, et al.
Network Neuroscience (Cambridge, Mass.)
|
June 30, 2021
Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach
Fernanda L Ribeiro, Felipe R C Dos Santos, João R Sato, et al.
Ebiomedicine
|
April 3, 2022
Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites
Kun Qin, Du Lei, Walter H L Pinaya, et al.
BMC Psychiatry
|
October 29, 2021
Using deep learning to classify pediatric posttraumatic stress disorder at the individual level
Jing Yang, Du Lei, Kun Qin, et al.
Journal of Medical Imaging (Bellingham, Wash.)
|
June 30, 2025
Simulating dynamic tumor contrast enhancement in breast MRI using conditional generative adversarial networks
Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou, et al.
Page
of 3