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Prehospital Injury Severity Estimate (PHISE) matches in-hospital trauma scores when embedded in AI models.

Trauma severity scores such as the Injury Severity Score (ISS) and New Injury Severity Score (NISS) are widely used for trauma benchmarking, risk stratification and outcome prediction, but rely on diagnostic imaging unavailable in the prehospital setting. We developed and externally validated the Prehospital Injury Severity Estimate (PHISE), a simple, scene-based score designed to be applied using...

Essential Innovations in Spinal Surgery: Contributions from the French School.

French innovation has profoundly shaped the evolution of spinal surgery over the past fifty years. While many French contributions are now internationally recognized, few studies have explored their impact on the biomechanical understanding of the spine, the development of surgical techniques, or their broader implications. This review aims to trace France's contributions to advancing spinal physi...

Predicting Outcomes of Traumatic Brain Injury Using Machine Learning Models Among Patients at Kilimanjaro Christian Medical Centre, Tanzania: A Registry-Based Cohort Study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health burden, disproportionately affecting low- and middle-income countries (LMICs) w...

AI-assisted post-mortem classification of vehicle trauma in free-roaming cats using transformer-based large language models.

Veterinary forensic science is a specialized discipline that investigates non-natural animal deaths and injuries. Determining the cause of death in fr...

Impact of guideline-based prompting on the large language model performance in dental trauma management clinical decision-making.

This study evaluated the impact of guideline-based prompting on the performance of large language models (LLMs) in answering dental trauma-related que...

Evaluation framework for assessing the quality and safety of artificial intelligence solutions for the acute care surgeon: a narrative review from the Eastern Association for the Surgery of Trauma quality, safety, and outcomes committee.

Artificial intelligence (AI) has been developing as a field for decades. As acute care surgeons, we have been using AI in the clinical realm and in ou...

Transforming Orthopaedic Trauma Care: Forecasting Operating Room Demand by Harnessing Time-Series Analysis and Machine Learning.

BACKGROUND: Efficient allocation of operating room (OR) time is critical in trauma centers, where unpredictable volumes lead to wasted resources. Fore...

Development and external validation of a machine learning model for predicting tigecycline-associated drug-induced liver injury.

Tigecycline (TGC) is widely used to treat severe multidrug-resistant infections but can cause drug-induced liver injury. Existing prediction studies f...

Comparative Assessment of Performance of Domain-Specific and Primed Versus Non-Primed Artificial Intelligence Chatbots for Clinical Decision-Making in Injuries to the Primary Dentition: An Exploratory Pilot Study.

BACKGROUND/AIMS: To compare the performance of a domain-specific dental trauma chatbot with general-purpose artificial intelligence chatbots under pri...

miR-124 Ameliorates Spatial Memory Deficits in Rats Exposed to Single-Prolonged Stress by Downregulating IQGAP1 to Regulate Actin-Binding Proteins and Apoptosis in Hippocampal Neurons.

Post-traumatic stress disorder (PTSD) is a highly prevalent, trauma-induced psychiatric condition characterized by persistent cognitive-affective dysf...

Measures matter: assessing childhood maltreatment and emotion dysregulation in a transdiagnostic sample.

Background: Childhood maltreatment (CM) is a major risk factor for different mental disorders and transdiagnostic mechanisms, including emotion dysreg...

Global burden of traumatic brain injury from 1990 to 2021 and projections to 2050: A GBD 2021-based study using interpretable machine learning.

Traumatic brain injury (TBI) is a major cause of disability and socioeconomic burden worldwide. Using updated Global Burden of Disease Study 2021 esti...

Beyond Thresholds: Can Machine Learning Improve Trauma Field Triage?

BackgroundAccurate triage of trauma patients by Emergency Medical Services (EMS) is essential for optimal outcomes and resource allocation. The 2021 N...

Evaluating performance and potential clinical benefit of the Swedish On Scene Injury Severity Prediction (OSISP) model for prehospital field triage on Norwegian trauma data.

BACKGROUND: Rule-based field triage protocols used by Emergency Medicine Service (EMS) personnel for assessment and prioritization of trauma patients ...

Zero-Shot Large Language Models for Preliminary Prediction of PTSD Symptoms From Clinical Interview Transcripts: Grands modèles de langage sans exemple pour la prédiction préliminaire des symptômes de TSPT à partir de transcriptions d'entrevues cliniques.

BackgroundPosttraumatic stress disorder (PTSD) is common yet frequently underdiagnosed, in part due to barriers to systematic screening and the relian...

Novel Musculoskeletal Hypotheses in the Armed Services Trauma and Rehabilitation Outcome (ADVANCE) Cohort: Development and Application of Sparse Group Factor Analysis Methodology.

BACKGROUND: Musculoskeletal conditions are a leading global cause of disability, yet the factors influencing long-term musculoskeletal health, particu...

Artificial intelligence for pediatric neuroimaging.

Artificial intelligence (AI) is revolutionizing health care, particularly in radiology for which large retrospective electronic datasets are naturally...

Language-dependent performance variation in large language models for dental trauma management: a comparative evaluation of ChatGPT-5.2, Gemini 3.0, and Claude 4.5 Sonnet.

BACKGROUND: Large language models (LLMs) are increasingly evaluated for medical question answering and clinical information tasks, yet the impact of q...

Impact of Artificial Intelligence Assistance on Diagnosing Traumatic Pneumothorax: A Comparison of Specialist and Non-Specialist Emergency Physicians.

INTRODUCTION: Supine chest radiography is routinely used in trauma care; however, its sensitivity is limited in pneumothorax detection. Although artif...

Enhancing the golden hour: classification of traumatic brain injury, severity, and concomitant clinical phenotypes using prehospital continuous physiological data during air transport.

During emergency transport, clinical assessment and vital signs may lack the sensitivity to identify traumatic brain injury (TBI) and identify specifi...