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Edith Pomarol-Clotet

Showing results (181-190 of 223) with videos related to

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Biological Psychiatry|February 20, 2026
The link between weight gain and hippocampal atrophy in bipolar disorder - A longitudinal investigation in 934 participantsJulia Fraiha-Pegado, Sean R McWhinney, Martin Alda, et al.
Scientific Reports|January 11, 2024
Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measuresVladimir Belov, Tracy Erwin-Grabner, Moji Aghajani, et al.
Biorxiv : the Preprint Server for Biology|November 14, 2023
Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA studyWolfgang Omlor, Finn Rabe, Simon Fuchs, et al.
Medrxiv : the Preprint Server for Health Sciences|April 20, 2026
Network and receptor architectures shape brain morphometry in addictionFoivos Georgiadis, Beatrice A Milano, Sara Larivière, et al.
Biological Psychiatry|November 23, 2021
Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working GroupChristoph Abé, Christopher R K Ching, Benny Liberg, et al.
Molecular Psychiatry|February 9, 2024
Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA studyFoivos Georgiadis, Sara Larivière, David Glahn, et al.
Neuroimage|May 30, 2020
Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMAJoaquim Radua, Eduard Vieta, Russell Shinohara, et al.
Molecular Psychiatry|September 2, 2018
Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working GroupAbraham Nunes, Hugo G Schnack, Christopher R K Ching, et al.
Machine Learning in Medical Imaging. MLMI (Workshop)|July 24, 2018
Machine Learning for Large-Scale Quality Control of 3D Shape Models in NeuroimagingDmitry Petrov, Boris A Gutman, Shih-Hua Julie Yu, et al.
Bipolar Disorders|December 11, 2021
Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individualsSean R McWhinney, Christoph Abé, Martin Alda, et al.
Pageof 23

Showing results (181-190 of 223) with videos related to

Sort By:
Pageof 23
Biological Psychiatry|February 20, 2026
The link between weight gain and hippocampal atrophy in bipolar disorder - A longitudinal investigation in 934 participantsJulia Fraiha-Pegado, Sean R McWhinney, Martin Alda, et al.
Scientific Reports|January 11, 2024
Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measuresVladimir Belov, Tracy Erwin-Grabner, Moji Aghajani, et al.
Biorxiv : the Preprint Server for Biology|November 14, 2023
Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA studyWolfgang Omlor, Finn Rabe, Simon Fuchs, et al.
Medrxiv : the Preprint Server for Health Sciences|April 20, 2026
Network and receptor architectures shape brain morphometry in addictionFoivos Georgiadis, Beatrice A Milano, Sara Larivière, et al.
Biological Psychiatry|November 23, 2021
Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working GroupChristoph Abé, Christopher R K Ching, Benny Liberg, et al.
Molecular Psychiatry|February 9, 2024
Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA studyFoivos Georgiadis, Sara Larivière, David Glahn, et al.
Neuroimage|May 30, 2020
Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMAJoaquim Radua, Eduard Vieta, Russell Shinohara, et al.
Molecular Psychiatry|September 2, 2018
Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working GroupAbraham Nunes, Hugo G Schnack, Christopher R K Ching, et al.
Machine Learning in Medical Imaging. MLMI (Workshop)|July 24, 2018
Machine Learning for Large-Scale Quality Control of 3D Shape Models in NeuroimagingDmitry Petrov, Boris A Gutman, Shih-Hua Julie Yu, et al.
Bipolar Disorders|December 11, 2021
Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individualsSean R McWhinney, Christoph Abé, Martin Alda, et al.
Pageof 23