Emergency Medicine

Latest AI and machine learning research in emergency medicine for healthcare professionals.

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Showing 568-588 of 5,224 articles
Early prediction of intensive care unit admission in emergency department patients using machine learning.

BACKGROUND: The timely identification and transfer of critically ill patients from the emergency dep...

Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence.

OBJECTIVES: We aim to evaluate the accuracy of radiologists and radiology residents in the detection...

Prediction of Brain Cancer Occurrence and Risk Assessment of Brain Hemorrhage Using Hybrid Deep Learning Technique.

The prediction of brain cancer occurrence and risk assessment of brain hemorrhage using a hybrid dee...

Prediction of prolonged mechanical ventilation in the intensive care unit via machine learning: a COVID-19 perspective.

Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early c...

PREDICTING IN-HOSPITAL MORTALITY IN CRITICAL ORTHOPEDIC TRAUMA PATIENTS WITH SEPSIS USING MACHINE LEARNING MODELS.

Purpose: This study aims to establish and validate machine learning-based models to predict death in...

Machine Learning-based Prediction of Blood Stream Infection in Pediatric Febrile Neutropenia.

OBJECTIVES: This study aimed to develop machine learning (ML) prediction models for identifying bloo...

Application of machine learning to identify risk factors for outpatient opioid prescriptions following spine surgery.

INTRODUCTION: Spine surgery is a common source of narcotic prescriptions and carries potential for l...

Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction.

BACKGROUND: Opioid addiction is a worldwide public health crisis. In the United States, for example,...

Evaluating the Utility of ChatGPT in Diagnosing and Managing Maxillofacial Trauma.

Maxillofacial trauma is a significant concern in emergency departments (EDs) due to its high prevale...

Identification of immune-related mitochondrial metabolic disorder genes in septic shock using bioinformatics and machine learning.

PURPOSE: Mitochondria are involved in septic shock and inflammatory response syndrome, which severel...

External validation and performance analysis of a deep learning-based model for the detection of intracranial hemorrhage.

PurposeWe aimed to investigate the external validation and performance of an FDA-approved deep learn...

Bonevoyage: Navigating the depths of osteoporosis detection with a dual-core ensemble of cascaded ShuffleNet and neural networks.

BACKGROUND: Osteoporosis (OP) is a condition that significantly decreases bone density and strength,...

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