Sexual Assault

Detection of Posttraumatic Stress Disorder With Rest-Activity Data: Machine Learning Approach Using Wearable and Self-Report Data.

BACKGROUND: Growing evidence suggests that disruptions in rest-activity rhythms may serve as relevant markers of posttraumatic stress disorder (PTSD). Despite the emergence of machine learning methods applied to actigraphy and self-report data, few studies have used these approaches to identify individuals with clinically diagnosed PTSD. Prior work has focused on predicting probable PTSD based on ...

Exploring the Psychological Mechanisms of Self-Aggression in Male Individuals with Substance Use Disorders: A Study Combining Interpretability Automated Machine Learning and Conditional Process Model.

Background: Individuals with substance use disorders often exhibit self-aggressive behaviors, which are linked to childhood trauma, the psychological mechanisms underlying self-aggression in substance use disorders remain unclear. This study utilizes key features extracted based on feature importance from explainable machine learning to establish a conditional process model, exploring significant ...

Diagnostic accuracy of AI-assisted point-of-care ultrasound for abdominal free fluid detection in FAST trauma assessment: a systematic review and meta-analysis.

STUDY OBJECTIVE: Point-of-care ultrasound (PoCUS) is widely used in trauma care through the Focused Assessment with Sonography for Trauma (FAST) proto...

Metabolomics at the Crossroads of Forensic Toxicology and Precision Diagnostics: Analytical Innovations and Translational Opportunities.

Metabolomics is the comprehensive analysis of small-molecule metabolites in living systems and is increasingly being applied in forensic science and h...

Inflammatory-neurodegenerative crosstalk in pediatric severe traumatic brain injury: a multi-domain plasma proteomic study.

BACKGROUND: Pediatric severe traumatic brain injury (sTBI) remains a leading cause of death and long-term disability, yet its molecular characterizati...

Molecular mechanism leading to human coronary atherosclerosis assessed by proteomic analysis and RNA sequences.

BACKGROUND AND AIMS: Atherosclerosis results from cellular and extracellular changes in the arterial wall, preceded by molecular shifts that initiate ...

State of the Art: Scapholunate Ligament Injuries.

ABSTRACT: Scapholunate ligament injuries are the most common ligamentous injuries of the wrist and typically result from high-energy trauma, most ofte...

Childhood environment clusters reveal heterogeneous associations between large-scale brain networks and youth mental health symptoms.

BACKGROUND: Youth mental health and brain development are profoundly shaped by highly heterogeneous childhood environments. However, research often op...

[Use of artificial intelligence for next-gen anamnesis and communication in orthopedics & trauma surgery : From chatbots to ambient intelligence].

BACKGROUND: Against the backdrop of increasing patient volumes, rising case complexity, and physicians' limited time, AI-driven systems for anamnesis,...

Machine Learning-Based Prediction Model for Infectious Complications in Trauma and Its Association With In-Hospital Mortality.

BACKGROUND: Infectious complications, such as sepsis or catheter-related infections, are common and serious sequelae after trauma. Despite their clini...

[Writing with a system-ChatGPT in the scientific practice of orthopedics and trauma surgery].

With the emergence of generative AI models such as ChatGPT, a new phase of scientific work is also beginning in orthopedics and trauma surgery. As a l...

Can a Large Language Model Grounded in Text-Based Agency-Specific Prehospital Protocols Provide Accurate Care Recommendations?

OBJECTIVES: Large language models (LLMs) using a retrieval-augmented generation (RAG) approach have the ability to respond to user queries with answer...

Hybrid model based on fuzzy logic and classification trees for the prediction of mortality of critical trauma patients: Pre-hospital variables from the RETRAUCI registry.

BACKGROUND: In critically injured trauma patients, tools that stratify injury severity and estimate mortality are essential. Fuzzy logic (FL) enables ...

Examining the utility of digital phenotyping for the prediction of intrusive experiences.

Background: Intrusive experiences related to witnessing a traumatic event are the core symptom of post-traumatic stress disorder (PTSD), and have been...

Geometric Morphometric-Based Estimation as an Aid for Naso-Orbito-Ethmoidal Trauma Management.

The naso-orbito-ethmoid (NOE) region comprises complex anatomy, and as such, NOE fractures present with a challenge during reconstruction. Restoring t...

Artificial Intelligence in the Trauma Bay: A Pilot Comparison With Surgical Trainees.

BackgroundLarge language models (LLMs) have demonstrated strong performance on general medical knowledge assessments; however, their accuracy within h...

Breaking the Black Box: Interpretable AI Achieves Superior Hemorrhage Detection with the Compensatory Reserve Measurement.

Hemorrhage remains the leading cause of preventable trauma death, with traditional vital signs failing to detect blood loss until 25-30% volume deplet...

Artificial Intelligence-Based Analysis of Laparoscopic Imaging for Intraoperative Surgical Decision Support.

Across surgical specialties, minimally invasive (laparoscopic) surgery has become a standard technique, as it is associated with less trauma, reduced ...

Editorial: future of ureteral stents: what do we need? a pearls opinion.

Ureteral stents, introduced in 1960s, are essential for managing upper urinary tract pathologies, maintaining ureteral patency in conditions like obst...

Evaluation of an AI-Driven Risk Stratification System for Clinical Deterioration in Geriatric Hip Fracture Patients.

OBJECTIVES: To determine whether an artificial-intelligence-driven Clinical Deterioration Index (CDI) could identify geriatric hip-fracture patients a...