Post-traumatic stress disorder: clinical and translational neuroscience from cells to circuits

KJ Ressler, S Berretta, VY Bolshakov… - Nature Reviews …, 2022 - nature.com
Post-traumatic stress disorder (PTSD) is a maladaptive and debilitating psychiatric disorder,
characterized by re-experiencing, avoidance, negative emotions and thoughts, and …

Applications of artificial intelligence− machine learning for detection of stress: a critical overview

AFA Mentis, D Lee, P Roussos - Molecular Psychiatry, 2024 - nature.com
Psychological distress is a major contributor to human physiology and pathophysiology, and
it has been linked to several conditions, such as auto-immune diseases, metabolic …

Machine learning for post‐traumatic stress disorder identification utilizing resting‐state functional magnetic resonance imaging

T Saba, A Rehman, MN Shahzad, R Latif… - Microscopy …, 2022 - Wiley Online Library
Early detection of post‐traumatic stress disorder (PTSD) is essential for proper treatment of
the patients to recover from this disorder. The aligned purpose of this study was to …

Predicting PTSD symptoms in firefighters using a fear-potentiated startle paradigm and machine learning

Y Li, N Li, L Zhang, Y Liu, T Zhang, D Li, D Bai… - Journal of affective …, 2022 - Elsevier
This study develops a fear-potentiated startle paradigm (FPS) and a machine learning
approach to accurately predict PTSD symptoms using electrogram data. A three-phase fear …

Linguistic markers of anxiety and depression in Somatic Symptom and Related Disorders: Observational study of a digital intervention

M Malgaroli, TD Hull, A Calderon, NM Simon - Journal of Affective …, 2024 - Elsevier
Abstract Background Somatic Symptom and Related Disorders (SSRD), including chronic
pain, result in frequent primary care visits, depression and anxiety symptoms, and …

Resolving Heterogeneity in Posttraumatic Stress Disorder Using Individualized Structural Covariance Network Analysis

X Suo, N Pan, L Chen, L Li, GJ Kemp… - Depression and …, 2024 - Wiley Online Library
The heterogeneity of posttraumatic stress disorder (PTSD) is an obstacle to both
understanding and therapy, and this has prompted a search for internally homogeneous …

Machine learning models predict PTSD severity and functional impairment: A personalized medicine approach for uncovering complex associations among …

AH Park, H Patel, J Mirabelli, SJ Eder… - … , Practice, and Policy, 2023 - psycnet.apa.org
Objective: Posttraumatic stress disorder (PTSD) is a debilitating psychiatric illness,
experienced by approximately 10% of the population. Heterogeneous presentations that …

Prefrontal metabolite alterations in individuals with posttraumatic stress disorder: a 7T magnetic resonance spectroscopy study

MA Reid, SE Whiteman, AA Camden… - Chronic …, 2024 - journals.sagepub.com
Background Evidence from animal and human studies suggests glutamatergic dysfunction
in posttraumatic stress disorder (PTSD). The purpose of this study was to investigate …

Tr-estimate: a novel machine learning based early prediction system for post-traumatic stress disorder using IoMT

L Rachakonda, KC Bipin - 2022 IEEE International Symposium …, 2022 - ieeexplore.ieee.org
A mental condition that develops after exposure to a threatening event is called post-
traumatic stress disorder (PTSD). The symptoms and impact of this disorder can be …

[HTML][HTML] Artificial Intelligence in Psychiatry: A Review of Biological and Behavioral Data Analyses

İ Baydili, B Tasci, G Tasci - Diagnostics, 2025 - mdpi.com
Artificial intelligence (AI) has emerged as a transformative force in psychiatry, improving
diagnostic precision, treatment personalization, and early intervention through advanced …