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This study used machine learning methods to examine features from 26 posttraumatic symptoms assessed during the first 8 weeks following traumatic exposure in order to develop a pragmatic algorithm to predict PTSD. The resulting algorithm accurately predicted PTSD and contained the mean scores from three items: nervousness, re-hashing, and fatigue.

This pilot implementation study outlines a curriculum on digital psychiatry at a large US-based psychiatry residency training program, including an evaluation of learner confidence in the appraisal and clinical recommendation of digital mental health apps.

ShapeAXI is a framework for shape analysis that uses a multi-view approach, capturing 3D objects from various angles and analyzing them with 2D CNNs. It features an automatic N-fold cross-validation process and generates explainability heat-maps, demonstrating its effectiveness in classifying condyles and cleft patient shapes, with its implementation available on...

The current study developed and validated a brief bedside screening tool that could be used with recent sexual assault survivors to understand who is at risk for chronic and impairing posttraumatic stress (PTS) and could benefit from early intervention. The sample included 547 women presenting to one of thirteen hospitals...

Dynamic functional network connectivity (dFNC) analysis is a widely used approach for studying brain function and offering insight into how brain networks evolve over time. Functional dysconnectivity between different brain regions has been reported in schizophrenia, yet the neural mechanisms behind it remain elusive. This manuscript presents a complementary novel...

Post-traumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly comorbid and individual differences in response to stress suggest resilient and susceptible populations. The current review discusses the advantages of using predator odor stressors to better understand PTSD pathophysiology and neurobiological mechanisms associated with stress reactivity and subsequent increases...

Control over internal representations requires the prioritization of relevant information and suppression of irrelevant information. We used TMS while participants either prioritized or suppressed information during a working memory task. We found evidence to support the idea that the frontoparietal theta network prioritizes internally maintained representations and alpha oscillations in...

This review emphasizes the significant therapeutic potential of neuroactive steroids in modulating TLR signaling pathways, particularly in addressing inflammatory processes associated with neuropsychiatric disorders. It advances our understanding of the complex interplay between neuroactive steroids and immune responses, paving the way for personalized treatment strategies tailored to individual needs and...