Emergency Medicine

Spatiotemporal clustering of state-level opioid, opioid-stimulant, and opioid-benzodiazepine polysubstance deaths across the U.S.: Hierarchical agglomerative clustering analysis.

BACKGROUND: Polysubstance use continues to complicate the US overdose landscape, with over 107,000 lives lost to drug overdoses in 2022. The present study uses hierarchical agglomerative clustering to identify distinct spatiotemporal profiles of opioid-only, opioid-stimulant, and opioid-benzodiazepine overdose deaths. METHODS: We used de-identified data sourced from the CDC's WONDER Multiple Cause...

Automated auditing of emergency department documentation using large language models.

INTRODUCTION: Errors in emergency department (ED) documentation can lead to patient harm and medicolegal risk, however manual document auditing is resource-intensive and difficult to scale. Large language models (LLMs) may offer an automated alternative, but their performance for task-specific error detection remains uncertain. This study evaluated four state-of-the-art LLMs for automated auditing...

Modern machine learning techniques used in prediction of sepsis and bloodstream infection in burn patients: A systematic review.

INTRODUCTION: Burn patients are a group highly prone to sepsis and bloodstream infections (BSIs) due to immune dysregulation, skin barrier loss, and c...

Validation of the Eyerobo FC Portable Fundus Camera for Diabetic Retinopathy Screening Using Public Datasets and Deep Learning.

INTRODUCTION: To validate the diagnostic performance of the Eyerobo FC, a new portable non-mydriatic fundus camera for diabetic retinopathy (DR) scree...

Pinostrobin attenuates microglia-mediated neuroinflammation after subarachnoid hemorrhage through modulation of the MYC-CTSL signaling axis.

Subarachnoid hemorrhage (SAH) is a life-threatening neurological emergency associated with high mortality and poor functional outcomes. Early brain in...

Letter to the Editor: Artificial intelligence in radiology: diagnostic sensitivity of ChatGPT for detecting hemorrhages in cranial computed tomography scans.

Method design and automation of a forensic toxicology LC-QTOF-MS technique to meet high-throughput routine applications.

The utility of a comprehensive and validated analytical technique is minimized without a holistic method design and automated data processing. Forensi...

ResNet based backbone integrated YOLO framework for bone fracture detection.

The usage of artificial intelligence and machine learning has significantly strengthened computer-aided medical diagnostics, and fine-tuning models an...

Machine learning-based model for triage-stage prediction of emergency department disposition.

Cross-Platform Proteomics and Machine Learning Algorithms Nominate Plasma Biomarkers of Stroke Diagnosis.

BACKGROUND: Blood-based biomarkers for stroke subtyping could improve triage in emergency settings. We used cross-platform proteomics to identify plas...

AI-Aided Triage for GSWH: Validating an Interpretable HCT-Based Mortality Model.

Civilian gunshot wounds to the head (GSWH) carry high mortality yet lack standardized, imaging-based triage tools. Because initial noncontrast head co...

Artificial Intelligence Models for Predicting Triage in Emergency Departments: Seven-Month Retrospective Comparative Study of Natural Language Processing, Large Language Model, and Joint Embedding Predictive Architectures.

BACKGROUND: Triage errors in emergency departments (EDs), including undertriage and overtriage, pose significant risks to patient safety and resource ...

Clinical implementation of AI for vertebral fracture detection in CT aligned with fracture liaison services: high prevalence of undiagnosed vertebral fractures.

UNLABELLED: We assessed feasibility and effectiveness of AI-based VF screening in CT, integrated with a local FLS. The system identified VFs in 14% of...

Non-contact monitoring in neonatology.

To present and critically evaluate current contactless monitoring modalities - infrared thermography (IRT), photoplethysmography imaging (PPGI), balli...

Risk prediction modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: leveraging machine learning.

BACKGROUND: Preprocedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-makin...

Clinical Impact of Postrecanalization Hemorrhagic Transformation and Its Prediction Using Baseline Noncontrast CT.

BACKGROUND: Hemorrhagic transformation (HT) after recanalization therapy remains a critical concern in acute ischemic stroke management. While severe ...

Predictive modeling of composite fracture toughness using machine learning.

OBJECTIVES: This study applied machine learning (ML) models to predict fracture toughness (K1c) of experimental ion-releasing resin-based composites a...

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern....

Benchmarking a deep learning model against healthcare practitioners for hip fracture detection in the emergency department.

INTRODUCTION: This study aimed to validate a deep learning (DL) model for automated hip fracture detection on pelvic X-rays in emergency departments (...

Artificial intelligence and robotics in global neurosurgery: A scoping review.

OBJECTIVE: Artificial intelligence (AI) and robotics are transforming neurosurgical care; however, the application of these technologies in low- and m...