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Patrick H Luckett

Showing results (1-10 of 23) with videos related to

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Human Brain Mapping|August 26, 2024
Complexity organization of resting-state functional-MRI networksGabriel Trevino, John J Lee, Joshua S Shimony, et al.
Journal of Neuro-Oncology|May 28, 2026
Predicting progression-free survival in glioblastoma with neuroimaging and machine learningDavin A Hickman-Chow, Patrick H Luckett, Michael Olufawo, et al.
Journal of Neuro-Oncology|January 6, 2026
BOLD complexity characterizes glioblastoma survival via voxel-wise and localized sample entropyMengqi Gu, Patrick H Luckett, Michael Olufawo, et al.
Alzheimer'S & Dementia (Amsterdam, Netherlands)|April 8, 2026
Application of machine learning to blood-based biomarkers of Alzheimer's disease in Down syndromePatrick H Luckett, Melissa Petersen, Sid O'Bryant, et al.
Imaging Neuroscience (Cambridge, Mass.)|September 8, 2025
Deep learning-based embedding of functional connectivity profiles for precision functional mappingJiaxin Cindy Tu, Jung-Hoon Kim, Chenyan Lu, et al.
Journal of Acquired Immune Deficiency Syndromes (1999)|August 18, 2021
Modeling the Effects of HIV and Aging on Resting-State Networks Using Machine LearningPatrick H Luckett, Robert H Paul, Kayla Hannon, et al.
Neuroimage. Clinical|July 15, 2023
Glioblastoma induces whole-brain spectral change in resting state fMRI: Associations with clinical comorbidities and overall survivalKi Yun Park, Abraham Z Snyder, Michael Olufawo, et al.
Epilepsia|March 23, 2022
Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsyPatrick H Luckett, Luigi Maccotta, John J Lee, et al.
Journal of Neurosurgery|April 15, 2023
Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learningPatrick H Luckett, Ki Yun Park, John J Lee, et al.
Frontiers in Neurology|January 30, 2023
Resting state network mapping in individuals using deep learningPatrick H Luckett, John J Lee, Ki Yun Park, et al.
Pageof 3

Showing results (1-10 of 23) with videos related to

Sort By:
Pageof 3
Human Brain Mapping|August 26, 2024
Complexity organization of resting-state functional-MRI networksGabriel Trevino, John J Lee, Joshua S Shimony, et al.
Journal of Neuro-Oncology|May 28, 2026
Predicting progression-free survival in glioblastoma with neuroimaging and machine learningDavin A Hickman-Chow, Patrick H Luckett, Michael Olufawo, et al.
Journal of Neuro-Oncology|January 6, 2026
BOLD complexity characterizes glioblastoma survival via voxel-wise and localized sample entropyMengqi Gu, Patrick H Luckett, Michael Olufawo, et al.
Alzheimer'S & Dementia (Amsterdam, Netherlands)|April 8, 2026
Application of machine learning to blood-based biomarkers of Alzheimer's disease in Down syndromePatrick H Luckett, Melissa Petersen, Sid O'Bryant, et al.
Imaging Neuroscience (Cambridge, Mass.)|September 8, 2025
Deep learning-based embedding of functional connectivity profiles for precision functional mappingJiaxin Cindy Tu, Jung-Hoon Kim, Chenyan Lu, et al.
Journal of Acquired Immune Deficiency Syndromes (1999)|August 18, 2021
Modeling the Effects of HIV and Aging on Resting-State Networks Using Machine LearningPatrick H Luckett, Robert H Paul, Kayla Hannon, et al.
Neuroimage. Clinical|July 15, 2023
Glioblastoma induces whole-brain spectral change in resting state fMRI: Associations with clinical comorbidities and overall survivalKi Yun Park, Abraham Z Snyder, Michael Olufawo, et al.
Epilepsia|March 23, 2022
Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsyPatrick H Luckett, Luigi Maccotta, John J Lee, et al.
Journal of Neurosurgery|April 15, 2023
Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learningPatrick H Luckett, Ki Yun Park, John J Lee, et al.
Frontiers in Neurology|January 30, 2023
Resting state network mapping in individuals using deep learningPatrick H Luckett, John J Lee, Ki Yun Park, et al.
Pageof 3