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Michael Milham

Showing results (1-10 of 44) with videos related to

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Neuroimage|May 8, 2020
Towards clinical applications of movie fMRISimon B Eickhoff, Michael Milham, Tamara Vanderwal
Gigascience|March 12, 2022
How to remove or control confounds in predictive models, with applications to brain biomarkersDarya Chyzhyk, Gaël Varoquaux, Michael Milham, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 11, 2021
Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral FeaturesDung Truong, Michael Milham, Scott Makeig, et al.
Journal of the American Academy of Child and Adolescent Psychiatry|February 11, 2020
Computer-Assisted Psychiatric DiagnosisKenneth Kobak, Lisa Townsend, Boris Birmaher, et al.
Biomed Research International|July 15, 2015
Toward a Meta-Analytic Synthesis of the Resting-State fMRI Literature for Clinical PopulationsYu-Feng Zang, Xi-Nian Zuo, Michael Milham, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
A streamable large-scale clinical EEG dataset for Deep LearningDung Truong, Manisha Sinha, Kannan Umadevi Venkataraju, et al.
Computational Brain & Behavior|August 9, 2021
Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit TaskLilla Horvath, Stanley Colcombe, Michael Milham, et al.
Neuroimage|March 3, 2020
Bagging improves reproducibility of functional parcellation of the human brainAki Nikolaidis, Anibal Solon Heinsfeld, Ting Xu, et al.
Neuroimage|March 6, 2019
Benchmarking functional connectome-based predictive models for resting-state fMRIKamalaker Dadi, Mehdi Rahim, Alexandre Abraham, et al.
Neuroimage|May 8, 2018
Patterns of thought: Population variation in the associations between large-scale network organisation and self-reported experiences at restHao-Ting Wang, Danilo Bzdok, Daniel Margulies, et al.
Pageof 5

Showing results (1-10 of 44) with videos related to

Sort By:
Pageof 5
Neuroimage|May 8, 2020
Towards clinical applications of movie fMRISimon B Eickhoff, Michael Milham, Tamara Vanderwal
Gigascience|March 12, 2022
How to remove or control confounds in predictive models, with applications to brain biomarkersDarya Chyzhyk, Gaël Varoquaux, Michael Milham, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 11, 2021
Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral FeaturesDung Truong, Michael Milham, Scott Makeig, et al.
Journal of the American Academy of Child and Adolescent Psychiatry|February 11, 2020
Computer-Assisted Psychiatric DiagnosisKenneth Kobak, Lisa Townsend, Boris Birmaher, et al.
Biomed Research International|July 15, 2015
Toward a Meta-Analytic Synthesis of the Resting-State fMRI Literature for Clinical PopulationsYu-Feng Zang, Xi-Nian Zuo, Michael Milham, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
A streamable large-scale clinical EEG dataset for Deep LearningDung Truong, Manisha Sinha, Kannan Umadevi Venkataraju, et al.
Computational Brain & Behavior|August 9, 2021
Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit TaskLilla Horvath, Stanley Colcombe, Michael Milham, et al.
Neuroimage|March 3, 2020
Bagging improves reproducibility of functional parcellation of the human brainAki Nikolaidis, Anibal Solon Heinsfeld, Ting Xu, et al.
Neuroimage|March 6, 2019
Benchmarking functional connectome-based predictive models for resting-state fMRIKamalaker Dadi, Mehdi Rahim, Alexandre Abraham, et al.
Neuroimage|May 8, 2018
Patterns of thought: Population variation in the associations between large-scale network organisation and self-reported experiences at restHao-Ting Wang, Danilo Bzdok, Daniel Margulies, et al.
Pageof 5