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Sage Hahn

Showing results (1-10 of 18) with videos related to

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Jvs-Vascular Science|October 7, 2021
Machine deep learning accurately detects endoleak after endovascular abdominal aortic aneurysm repairSage Hahn, Mark Perry, Christopher S Morris, et al.
Bioinformatics (Oxford, England)|November 20, 2020
Brain Predictability toolbox: a Python library for neuroimaging-based machine learningSage Hahn, De Kang Yuan, Wesley K Thompson, et al.
Human Brain Mapping|December 19, 2022
Machine learning approaches linking brain function to behavior in the ABCD STOP taskDekang Yuan, Sage Hahn, Nicholas Allgaier, et al.
Cerebral Cortex (New York, N.Y. : 1991)|March 3, 2022
Performance scaling for structural MRI surface parcellations: a machine learning analysis in the ABCD StudySage Hahn, Max M Owens, DeKang Yuan, et al.
Cerebral Cortex (New York, N.Y. : 1991)|June 28, 2020
Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in ChildrenMax M Owens, DeKang Yuan, Sage Hahn, et al.
Experimental and Clinical Psychopharmacology|December 16, 2021
One-year predictions of delayed reward discounting in the adolescent brain cognitive development studyMax M Owens, Sage Hahn, Nicholas Allgaier, et al.
Pediatric Obesity|October 18, 2022
Longitudinal assessment of brain structure and behaviour in youth with rapid weight gain: Potential contributing causes and consequencesShana Adise, Andrew T Marshall, Sage Hahn, et al.
Translational Psychiatry|April 13, 2021
Correction to: Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD studyMax M Owens, Nicholas Allgaier, Sage Hahn, et al.
Journal of Abnormal Psychology|September 8, 2020
Neuroanatomical correlates of impulsive traits in children aged 9 to 10Max M Owens, Courtland S Hyatt, Joshua C Gray, et al.
Plos One|September 23, 2021
Recalibrating expectations about effect size: A multi-method survey of effect sizes in the ABCD studyMax M Owens, Alexandra Potter, Courtland S Hyatt, et al.
Pageof 2

Showing results (1-10 of 18) with videos related to

Sort By:
Pageof 2
Jvs-Vascular Science|October 7, 2021
Machine deep learning accurately detects endoleak after endovascular abdominal aortic aneurysm repairSage Hahn, Mark Perry, Christopher S Morris, et al.
Bioinformatics (Oxford, England)|November 20, 2020
Brain Predictability toolbox: a Python library for neuroimaging-based machine learningSage Hahn, De Kang Yuan, Wesley K Thompson, et al.
Human Brain Mapping|December 19, 2022
Machine learning approaches linking brain function to behavior in the ABCD STOP taskDekang Yuan, Sage Hahn, Nicholas Allgaier, et al.
Cerebral Cortex (New York, N.Y. : 1991)|March 3, 2022
Performance scaling for structural MRI surface parcellations: a machine learning analysis in the ABCD StudySage Hahn, Max M Owens, DeKang Yuan, et al.
Cerebral Cortex (New York, N.Y. : 1991)|June 28, 2020
Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in ChildrenMax M Owens, DeKang Yuan, Sage Hahn, et al.
Experimental and Clinical Psychopharmacology|December 16, 2021
One-year predictions of delayed reward discounting in the adolescent brain cognitive development studyMax M Owens, Sage Hahn, Nicholas Allgaier, et al.
Pediatric Obesity|October 18, 2022
Longitudinal assessment of brain structure and behaviour in youth with rapid weight gain: Potential contributing causes and consequencesShana Adise, Andrew T Marshall, Sage Hahn, et al.
Translational Psychiatry|April 13, 2021
Correction to: Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD studyMax M Owens, Nicholas Allgaier, Sage Hahn, et al.
Journal of Abnormal Psychology|September 8, 2020
Neuroanatomical correlates of impulsive traits in children aged 9 to 10Max M Owens, Courtland S Hyatt, Joshua C Gray, et al.
Plos One|September 23, 2021
Recalibrating expectations about effect size: A multi-method survey of effect sizes in the ABCD studyMax M Owens, Alexandra Potter, Courtland S Hyatt, et al.
Pageof 2