Emergency Medicine

From Outbreaks to Artificial Intelligence: A Comprehensive Review of Monkeypox Virus Epidemiology, Diagnosis, Treatment, Vaccination, and Deep Learning Applications.

After the global impact of the COVID-19 pandemic, concerns over virus transmission have risen. A state of health emergency was declared in 2022 due to Clade 2 of the monkeypox (MPOX) virus. In August 2024, another emergency was declared by the World Health Organization (WHO) because of the widespread Clade 1b, which caused a more severe and lethal disease. This review synthesizes current MPOX kno...

Evaluation of the effect of cell freshness on pyrogen detection using a serum-free monocyte-activation test.

Pyrogens cause shock symptoms when released into the bloodstream. They are classified into two main categories: endotoxins (lipopolysaccharides [LPS]) and non-endotoxin pyrogens. The monocyte activation test (MAT) is an in vitro assay to detect pyrogens in human monocytes. Cells were incubated in the culture medium, and the cellular response, specifically the production of the inflammatory cytokin...

Early prediction of functional impairment at hospital discharge in patients with osteoporotic vertebral fracture: a machine learning approach.

Although conservative treatment is commonly used for osteoporotic vertebral fracture (OVF), some patients experience functional disability following O...

Development of a Self-Deploying Extra-Aortic Compression Device for Medium-Term Hemodynamic Stabilization: A Feasibility Study.

Hemodynamic stabilization is crucial in managing acute cardiac events, where compromised blood flow can lead to severe complications and increased mor...

A novel interpretable deep learning model for diagnosis in emergency department dyspnoea patients based on complete data from an entire health care system.

BACKGROUND: Dyspnoea is one of the emergency department's (ED) most common and deadly chief complaints, but frequently misdiagnosed and mistreated. We...

Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of patients and their kidneys. Here, we present a cas...

Immunohistochemistry-Free Enhanced Histopathology of the Rat Spleen Using Deep Learning.

Enhanced histopathology of the immune system uses a precise, compartment-specific, and semi-quantitative evaluation of lymphoid organs in toxicology s...

Machine learning-based pipeline for automated intracerebral hemorrhage and drain detection, quantification, and classification in non-enhanced CT images (NeuroDrAIn).

BACKGROUND AND PURPOSE: External drainage represents a well-established treatment option for acute intracerebral hemorrhage. The current standard of p...

Evaluation of cerebral blood flow after subarachnoid hemorrhage using near-field coupling and machine learning.

BackgroundBedside continuous monitoring of cerebral blood flow (CBF) has significant implications in guiding individualized management and improving t...

FDA-reviewed artificial intelligence-enabled products applicable to emergency medicine.

OBJECTIVE: To identify and assess artificial intelligence (AI)-enabled products reviewed by the U.S. Food and Drug Administration (FDA) that are poten...

Development of Nipple Trauma Evaluation System With Deep Learning.

BACKGROUND: No research has been conducted on the use of deep learning for breastfeeding support.

Artificial intelligence in emergency and trauma radiology: ASER AI/ML expert panel Delphi consensus statement on research guidelines, practices, and priorities.

BACKGROUND: Emergency/trauma radiology artificial intelligence (AI) is maturing along all stages of technology readiness, with research and developmen...

Machine-learning based prediction of appendicitis for patients presenting with acute abdominal pain at the emergency department.

BACKGROUND: Acute abdominal pain (AAP) constitutes 5-10% of all emergency department (ED) visits, with appendicitis being a prevalent AAP etiology oft...

Extension of an ICU-based noninvasive model to predict latent shock in the emergency department: an exploratory study.

BACKGROUND: Artificial intelligence (AI) has been widely adopted for the prediction of latent shock occurrence in critically ill patients in intensive...

Deep learning model for automated detection of fresh and old vertebral fractures on thoracolumbar CT.

PURPOSE: To develop a deep learning system for automatic segmentation of compression fracture vertebral bodies on thoracolumbar CT and differentiate b...

Advanced Mass-Spectra-Based Machine Learning for Predicting the Toxicity of Traditional Chinese Medicines.

Traditional Chinese medicine (TCM) has been a cornerstone of health care for centuries, valued for its preventive and therapeutic properties. However,...

Evaluating LLM-based generative AI tools in emergency triage: A comparative study of ChatGPT Plus, Copilot Pro, and triage nurses.

BACKGROUND: The number of emergency department (ED) visits has been on steady increase globally. Artificial Intelligence (AI) technologies, including ...

An explainable and supervised machine learning model for prediction of red blood cell transfusion in patients during hip fracture surgery.

AIM: The study aimed to develop a predictive model with machine learning (ML) algorithm, to predict and manage the need for red blood cell (RBC) trans...

Artificial intelligence in risk prediction and diagnosis of vertebral fractures.

With the increasing prevalence of vertebral fractures, accurate diagnosis and prognostication are essential. This study assesses the effectiveness of ...

Identification of Potential Drug Targets for the Treatment of Severe Burn Wounds from a Multi-Omics Perspective.

PURPOSE: Severe burns result in significant skin damage, impairing its primary role as an infection barrier and presenting substantial treatment chall...