Emergency Medicine

Added value of deep learning-based liver parenchymal CT volumetry for predicting major arterial injury after blunt hepatic trauma: a decision tree analysis.

PURPOSE: In patients presenting with blunt hepatic injury (BHI), the utility of CT for triage to hep...

A comparison of machine learning models versus clinical evaluation for mortality prediction in patients with sepsis.

INTRODUCTION: Patients with sepsis who present to an emergency department (ED) have highly variable ...

A unified machine learning approach to time series forecasting applied to demand at emergency departments.

BACKGROUND: There were 25.6 million attendances at Emergency Departments (EDs) in England in 2019 co...

In Search of an Optimal Subset of ECG Features to Augment the Diagnosis of Acute Coronary Syndrome at the Emergency Department.

Background Classical ST-T waveform changes on standard 12-lead ECG have limited sensitivity in detec...

Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study.

BACKGROUND: Passive leg raising (PLR) predicts fluid responsiveness in critical illness, although re...

Early detection of sepsis using artificial intelligence: a scoping review protocol.

BACKGROUND: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to...

Predicting Progression to Septic Shock in the Emergency Department Using an Externally Generalizable Machine-Learning Algorithm.

STUDY OBJECTIVE: Machine-learning algorithms allow improved prediction of sepsis syndromes in the em...

The Feature Ambiguity Mitigate Operator model helps improve bone fracture detection on X-ray radiograph.

This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, ...

Predicting adult neuroscience intensive care unit admission from emergency department triage using a retrospective, tabular-free text machine learning approach.

Early admission to the neurosciences intensive care unit (NSICU) is associated with improved patient...

Use of Machine Learning to Re-Assess Patterns of Multivariate Functional Recovery after Fluid Percussion Injury: Operation Brain Trauma Therapy.

Traumatic brain injury (TBI) is a leading cause of death and disability. Yet, despite immense resear...

An artificial neural network based mathematical model for a stochastic health care facility location problem.

This research is conducted to investigate the problem of locating the trauma centers and helicopters...

Deep learning shows good reliability for automatic segmentation and volume measurement of brain hemorrhage, intraventricular extension, and peripheral edema.

OBJECTIVES: To evaluate for the first time the performance of a deep learning method based on no-new...

Screening For Bone Marrow Cellularity Changes in Cynomolgus Macaques in Toxicology Safety Studies Using Artificial Intelligence Models.

Many compounds affect the cellularity of hematolymphoid organs including bone marrow. Toxicologic pa...

Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial.

IMPORTANCE: Emergency medical dispatchers fail to identify approximately 25% of cases of out-of-hosp...

Machine Learning in Emergency Medicine: Keys to Future Success.

Machine Learning Versus Usual Care for Diagnostic and Prognostic Prediction in the Emergency Department: A Systematic Review.

OBJECTIVE: Having shown promise in other medical fields, we sought to determine whether machine lear...

Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology.

Digital tissue image analysis is a computational method for analyzing whole-slide images and extract...

Deep Learning in Toxicologic Pathology: A New Approach to Evaluate Rodent Retinal Atrophy.

Quantification of retinal atrophy, caused by therapeutics and/or light, by manual measurement of ret...

Nursing documentation of symptoms is associated with higher risk of emergency department visits and hospitalizations in homecare patients.

BACKGROUND: Nurses often document patient symptoms in narrative notes.

Development of Inappropriate Vasopressin Secretion in Association With Lumbar Cerebrospinal Fluid Drainage in an Adult With Traumatic Basilar Skull Fracture.

OBJECTIVE: Hyponatremia associated with cerebrospinal fluid (CSF) drainage is primarily limited to p...

Improving ED Emergency Severity Index Acuity Assignment Using Machine Learning and Clinical Natural Language Processing.

INTRODUCTION: Triage is critical to mitigating the effect of increased volume by determining patient...