Emergency Medicine

AI detection of knee joint effusion from radiographs: Comparative accuracy of two commercial algorithms.

BACKGROUND: Knee joint effusion might indicate injury even without bony changes. Automated detection from radiographs could improve the sensitivity of AI algorithms. PURPOSE: To compare two commercially available AI algorithms, BoneView and RBfracture, in detecting knee joint effusion. MATERIAL AND METHODS: This retrospective study collected 123 lateral knee radiographs. Detection of knee joint ef...

From decision support to clinical integration: A scoping review of artificial intelligence in prehospital airway management.

BACKGROUND: Airway management is a critical component of prehospital emergency care, where rapid decision-making and procedural accuracy are essential for patient survival. In recent years, artificial intelligence has emerged as a promising tool. However, the current landscape and translational readiness of artificial intelligence applications in prehospital airway management remain unclear. OBJEC...

Rapid Multi-Parametric Quantitative MRI via Deep Learning-Based Synthetic-to-Real Reconstruction and 3D SSFP-MOLED Imaging.

Multi-parametric quantitative magnetic resonance imaging (mqMRI) holds significant clinical potential through multi-parametric tissue characterization...

Machine learning and multi-dimensional transcriptomics reveal the key molecular network of benzo(a)pyrene/NNK in promoting laryngeal cancer and develop prognostic models.

Benzo(a)pyrene (BaP) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), as typical environmental carcinogens, are widely present in tobacco smo...

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...

Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.

BACKGROUND: Emergency ventral hernia repair remains a challenging procedure due to patient instability, contaminated surgical fields, and heterogeneit...

[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 Predictive Model for Fever and Adverse Clinical Events in Hospitalized Pediatric Burn Patients.

Systemic inflammation after pediatric burn injury frequently causes fever, complicating early recognition of infectious complications. Improved risk-s...

Deep learning-enabled monitoring of postoperative fracture healing on serial radiographs: a 150-patient study using an enhanced YOLOv11 framework.

OBJECTIVES: To develop and validate a deep learning framework for classifying postoperative time-points as a proxy task for monitoring longitudinal fr...

Construction and verification of multimodal model for prognosis in elderly patients with aneurysmal subarachnoid hemorrhage.

OBJECTIVE: This study aimed to construct and validate an individualized prediction model for poor prognosis in elderly patients with Aneurysmal subara...

Systematic evaluation of the DeepSeek large language model for clinical diagnostic reasoning.

BACKGROUND: Artificial intelligence (AI) is undergoing an era of transformative advancement, particularly through the emergence of Transformer-based l...

Multiple Targets and Pathways Non-Monotonically Regulate Lung Squamous Cell Carcinoma Migration in Response to Phthalates.

Phthalates (PAEs) are widely used plasticizers that are increasingly linked to tumorigenesis. In this study, we integrated network toxicology and mach...

Digital emergency routing: analysis of feasibility, utilization, and equity implications.

BACKGROUND: Digital emergency care applications offer potential to reduce delays, enhance triage, and improve care coordination, yet evidence remains ...

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...

Impact of a Prototype Combining Recommender Functionality With Structured Documentation on Operator Performance in Calls to Medical Communication Centers: Quasi-Experimental Feasibility Study.

BACKGROUND: Management of contacts to medical communication centers relies heavily on clinical judgment, contextual understanding, and communication s...

Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks.

Adnexal cystic torsion is a gynecological emergency that requires prompt and accurate diagnosis followed by immediate surgical intervention to preserv...

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 ...

Smartphone-based lightweight AI system for real-time multiple anterior segment disease screening: development and real-world validation.

BACKGROUND: Anterior segment diseases are a major global cause of preventable blindness, especially in regions with limited access to specialized opht...