Emergency Medicine

Using machine learning to predict bacteremia in urgent care patients on the basis of triage data and laboratory results.

BACKGROUND: Despite advancements in antimicrobial therapies, bacteremia remains a life-threatening c...

Knowledge-based machine learning for predicting and understanding the androgen receptor (AR)-mediated reproductive toxicity in zebrafish.

Traditional methods for identifying endocrine-disrupting chemicals (EDCs) that activate androgen rec...

Machine learning value in the diagnosis of vertebral fractures: A systematic review and meta-analysis.

PURPOSE: To evaluate the diagnostic accuracy of machine learning (ML) in detecting vertebral fractur...

Comment on 'Deep learning-assisted detection and segmentation of intracranial hemorrhage in noncontrast computed tomography scans of acute stroke patients: a systematic review and meta-analysis'.

Hybrid clinical-radiomics model based on fully automatic segmentation for predicting the early expansion of spontaneous intracerebral hemorrhage: A multi-center study.

BACKGROUND: Early prediction of hematoma expansion (HE) is important for the development of therapeu...

AI and Big Data approaches to addressing the opioid crisis: a scoping review protocol.

INTRODUCTION: This paper outlines the steps necessary to assess the latest developments in artificia...

Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta.

Amelogenesis imperfecta (AI) is a genetic disease characterized by poor formation of tooth enamel. A...

Identification of immune-related biomarkers for intracerebral hemorrhage diagnosis based on RNA sequencing and machine learning.

BACKGROUND: Intracerebral hemorrhage (ICH) is a severe stroke subtype with high morbidity, disabilit...

Detecting pediatric appendicular fractures using artificial intelligence.

OBJECTIVE: The primary objective was to assess the diagnostic accuracy of a deep learning-based arti...

Backdoor attacks on unsupervised graph representation learning.

Unsupervised graph learning techniques have garnered increasing interest among researchers. These me...

Machine Learning Model Reveals Determinators for Admission to Acute Mental Health Wards From Emergency Department Presentations.

This research addresses the critical issue of identifying factors contributing to admissions to acut...

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning.

Accurate prediction of protein-ligand binding affinities is an essential challenge in structure-base...

Large language model application in emergency medicine and critical care.

In the rapidly evolving healthcare landscape, artificial intelligence (AI), particularly the large l...

Potential strength and weakness of artificial intelligence integration in emergency radiology: a review of diagnostic utilizations and applications in patient care optimization.

Artificial intelligence (AI) and its recent increasing healthcare integration has created both new o...

Investigation of emergency department abandonment rates using machine learning algorithms in a single centre study.

A critical problem that Emergency Departments (EDs) must address is overcrowding, as it causes exten...

Enhancing diagnosis: ensemble deep-learning model for fracture detection using X-ray images.

AIM: Orthopedic trauma results in the injury of bone joints and tendons of the body. A radiologist r...

Accurate diagnosis of acute appendicitis in the emergency department: an artificial intelligence-based approach.

The diagnosis of abdominal pain in emergency departments is challenging, and appendicitis is a commo...

2023 Industry Perceptions Survey on AI Adoption and Return on Investment.

This SIIM-sponsored 2023 report highlights an industry view on artificial intelligence adoption barr...

Deep Learning-Based Model for Non-invasive Hemoglobin Estimation via Body Parts Images: A Retrospective Analysis and a Prospective Emergency Department Study.

Anemia is a significant global health issue, affecting over a billion people worldwide, according to...

Predicting the Healing of Lower Extremity Fractures Using Wearable Ground Reaction Force Sensors and Machine Learning.

Lower extremity fractures pose challenges due to prolonged healing times and limited assessment meth...

Advancing Emergency Department Triage Prediction With Machine Learning to Optimize Triage for Abdominal Pain Surgery Patients.

BACKGROUND: The development of emergency department (ED) triage systems remains challenging in accur...