Emergency Medicine

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...

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...

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...

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.

Predicting anaerobic digestion stability in load-flexible operation using gas phase indicators and classification algorithms.

This study investigates early warning indicators for process instabilities in anaerobic digestion ca...

An oral robotic pill reliably and safely delivers teriparatide with high bioavailability in healthy volunteers: A phase 1 study.

AIMS: The incidence of osteoporosis is projected to exceed 70 million people over the age of 65 year...

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...

Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies.

OBJECTIVE: Determine the efficacy of commonly used approaches to handling missing and/or imbalanced ...

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...

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...

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...

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...

Can Artificial Intelligence Language Models Effectively Address Dental Trauma Questions?

BACKGROUND/AIM: Artificial intelligence (AI) chatbots, also known as large language models (LLMs), h...

Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.

INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool us...

Identification of the potential role of PANoptosis-related genes in burns via bioinformatic analyses and experimental validation.

BACKGROUND: The treatment of burns is highly challenging due to their complex pathophysiological mec...

Triage of Patient Messages Sent to the Eye Clinic via the Electronic Medical Record: A Comparative Study on AI and Human Triage Performance.

: Assess the ability of ChatGPT-4 (GPT-4) to effectively triage patient messages sent to the general...