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

Keyphrases

• Trauma Patients 100%
• Functional Magnetic Resonance Imaging 100%
• Posttraumatic Stress Disorder 100%
• Recent Trauma 100%
• Posttraumatic Stress Symptoms 100%
• Deep Learning Model 100%
• Symptom Trajectories 100%
• Emergency Room 20%
• Early Detection 20%
• Clinical Outcomes 20%
• Resting State 20%
• Biological Mechanisms 20%
• Single Patient 20%
• Brain Regions 20%
• MRI Data 20%
• Co-activation 20%
• Computational Methods 20%
• Algorithmic Approach 20%
• Encoder 20%
• Predictive Ability 20%
• Adults at Risk 20%
• Early Intervention 20%
• Patient Characterization 20%
• Analytical Techniques 20%
• State-based 20%
• Traumatic Events 20%
• Deep Learning Methods 20%
• Activation Map 20%
• Trauma Exposure 20%
• Posttraumatic Stress Disorder Symptom Clusters 20%
• Symptom Cluster 20%
• End-to-end Deep Learning 20%
• Clinical Path 20%
• Functional MRI Data 20%
• Post-traumatic Sequelae 20%
• Traumatic Life Events 20%
• Method Performance 20%
• Region Embedding 20%
• Multi-label Classification 20%
• FMRI Data 20%

Computer Science

• Traumatic Stress Disorder 100%
• Deep Learning Model 100%
• Trauma Survivor 100%
• Neural Network 11%
• Clinical Outcome 11%
• Early Detection 11%
• Computational Method 11%
• Deep Learning Method 11%
• Traumatic Event 11%
• Feature Map 11%
• Multi-Label Classification 11%

Neuroscience

• Functional Magnetic Resonance Imaging 100%
• Posttraumatic Stress Disorder 100%
• Neural Network 11%
• Brain Region 11%