Deep learning model of fMRI connectivity predicts PTSD symptom trajectories in recent trauma survivors-Reference-Cited by-同舟云学术

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Deep learning model of fMRI connectivity predicts PTSD symptom trajectories in recent trauma survivors

Published:2021-09 Issue: Volume:238 Page:118242
ISSN:1053-8119
Container-title:NeuroImage
language:en
Short-container-title:NeuroImage

Author:

Sheynin Shelly,Wolf Lior,Ben-Zion Ziv,Sheynin Jony,Reznik Shira,Keynan Jackob Nimrod,Admon Roee,Shalev Arieh,Hendler Talma,Liberzon Israel

Funder

Horizon 2020

European Research Council

National Institute of Mental Health

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference91 articles.

1. Imbalanced neural responsivity to risk and reward indicates stress vulnerability in humans;Admon;Cereb. Cortex,2013

2. Brain activity dissociates mentalization from motivation during an interpersonal competitive game;Assaf;Brain Imaging Behav.,2009

3. Neuroanatomical risk factors for post traumatic stress disorder (PTSD) in recent trauma survivors;Ben-Zion;Biol. Psychiatry,2019

4. Cognitive flexibility predicts PTSD symptoms: observational and interventional studies;Ben-Zion;Front. Psychiatry,2018

5. Neurobehavioral moderators of post-traumatic stress disorder (PTSD) trajectories: study protocol of a prospective MRI study of recent trauma survivors;Ben-Zion;Eur. J. Psychotraumatol.,2019

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2. Application of machine learning techniques in the diagnostic approach of PTSD using MRI neuroimaging data: A systematic review;Heliyon;2024-04

3. Graph theory-based analysis reveals neural anatomical network alterations in chronic post-traumatic stress disorder;Imaging Neuroscience;2024-04

4. A Blueprint for Next Generation of Clinical Trials in Precision Psychiatry;Comprehensive Precision Medicine;2024

5. Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium;NeuroImage;2023-12

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