Emergency Medicine

ChatGPT-supported patient triage with voice commands in the emergency department: A prospective multicenter study.

BACKGROUND: Triage aims to prioritize patients according to their medical urgency by accurately eval...

Exploratory cluster analysis of IL2Ra and associated biomarkers and complications after blunt chest trauma.

BACKGROUND: Rib fractures compromise approximately 40% of all fractures in the United States. Despit...

Risk Factors and Outcomes of Hemorrhagic Transformation in Acute Ischemic Stroke Following Thrombolysis: Analysis of a Single-Center Experience and Review of the Literature.

: This is a retrospective study conducted at the Clinical County Hospital of Craiova, Romania, provi...

Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or tria...

Toxicological evaluation of Artocarpus lacucha ethyl acetate extract: in vitro and in vivo assessment.

ETHNOPHARMACOLOGICAL RELEVANCE: Artocarpus lacucha Buch. -Ham. (syn. Artocarpus lakoocha) (A. lacuch...

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms.

Alga toxins have recently emerged as environmental risk factors to multiple human health issues. Mit...

Peripheral blood immune landscape and NXPE3 as a novel biomarker for hypertensive intracerebral hemorrhage risk prediction and targeted therapy.

We employed bulk RNA-seq and scRNA-seq techniques to analyze the immune dysregulation in patients wi...

Cost-Effectiveness Analysis of a Machine Learning-Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at Home: Retrospective Study.

BACKGROUND: Dependent older people or those losing their autonomy are at risk of emergency hospitali...

Utilizing machine learning and geographic analysis to improve Post-crash traffic injury management and emergency response systems.

Traffic injuries are a major public health concern globally. This study uses machine learning (ML) a...

Bridging Data Gaps in Emergency Care: The NIGHTINGALE Project and the Future of AI in Mass Casualty Management.

In the context of mass casualty incident (MCI) management, artificial intelligence (AI) represents a...

Domestic violence and childhood trauma among married women using machine learning approach: a cross-sectional study.

BACKGROUND: Globally, 27% of ever-partnered women aged 15-49 have experienced physical, sexual, or i...

The role of artificial intelligence in predicting injured structures based on clinical images of lacerations in the volar aspect of the hand and forearm.

INTRODUCTION: Recently introduced image processing capabilities of AI models, which are accessible t...

AI-enhanced resuscitation image production training: advancing diversity and inclusion with GPT-4o.

Improving the usability of large emergency 911 data reporting systems: A machine learning case study using emergency incident descriptions.

INTRODUCTION: Emergency 9-1-1 incident data are recorded voluntarily within fire-department-specific...

Prioritization strategies for non-target screening in environmental samples by chromatography - High-resolution mass spectrometry: A tutorial.

Non-target screening (NTS) using chromatography coupled to high-resolution mass spectrometry (HRMS),...

MetaGP: A generative foundation model integrating electronic health records and multimodal imaging for addressing unmet clinical needs.

Artificial intelligence makes strides in specialized diagnostics but faces challenges in complex cli...

A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features.

OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classificatio...

Communication challenges and experiences between parents and providers in South Korean paediatric emergency departments: a qualitative study to define AI-assisted communication agents.

OBJECTIVES: This study aimed to explore communication challenges between parents and healthcare prov...

Evaluation of correctness and reliability of GPT, Bard, and Bing chatbots' responses in basic life support scenarios.

Timely recognition and initiation of basic life support (BLS) before emergency medical services arri...

Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.

Disseminated intravascular coagulation (DIC) is a thrombo-hemorrhagic disorder that can be life-thre...

Updates in Neonatal Seizures.

Neonatal seizures are a common medical emergency, necessitating prompt treatment. The most common et...