Highlights•AI enables early detection and large-scale monitoring of stress-related
issues.•LLM improves stress detection using advanced natural language processing …

Background The algorithmic patient preference predictor (PPP) has been proposed to aid in
decision making for incapacitated patients in the absence of advanced directives. Ethical …

Importance Military deployment involves significant risk for life-threatening experiences that
can lead to posttraumatic stress disorder (PTSD). Accurate predeployment prediction of …

BackgroundPsychological trauma exposure and posttraumatic stress disorder (PTSD) have
been associated with advanced epigenetic age. However, whether epigenetic aging …

Objective: Posttraumatic stress disorder (PTSD) is a debilitating psychiatric illness,
experienced by approximately 10% of the population. Heterogeneous presentations that …

Anxiety sensitivity, or fear of anxious arousal, is cross-sectionally associated with a wide
array of adverse posttraumatic neuropsychiatric sequelae, including symptoms of …

There are significant challenges to identifying which individuals require intervention
following exposure to trauma, and a need for strategies to identify and provide individuals at …

BackgroundRacial/ethnic differences in mental health outcomes after a traumatic event have
been reported. Less is known about factors that explain these differences. We examined …

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 …

Background Effective preventive interventions for PTSD rely on early identification of
individuals at risk for develo** PTSD. To establish early post-trauma who are at risk, there …