Emergency Medicine

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

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FRAX Calculated without BMD Resulting in a Higher Fracture Risk Than That Calculated with BMD in Women with Early Breast Cancer.

BACKGROUND AND PURPOSE: The aim of this study was to investigate the importance of including the mea...

Critically Ill Recipients of Weight-Based Fluconazole Meeting Drug-Induced Liver Injury Network Criteria.

Fluconazole-associated liver injury is estimated to occur in <10% of patients; however, effect of w...

A Random Forest-Assisted Evolutionary Algorithm for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems.

Many real-world optimization problems can be solved by using the data-driven approach only, simply b...

Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence.

Exposure to a chemical is a critical consideration in the assessment of risk, as it adds real-world ...

Deep Learning in Drug Discovery and Medicine; Scratching the Surface.

The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cu...

Improving the Accuracy of Scores to Predict Gastrostomy after Intracerebral Hemorrhage with Machine Learning.

BACKGROUND: Gastrostomy placement after intracerebral hemorrhage indicates the need for continued me...

The Elephant in the Room: Outbreak of Carfentanil Deaths in Minnesota and the Importance of Multiagency Collaboration.

Over a three-month period in early 2017, the Hennepin County Medical Examiner's Office investigated ...

Incidence of Remote Cerebellar Hemorrhage in Patients with a Dural Tear during Spinal Surgery: A Retrospective Observational Analysis.

INTRODUCTION: The incidence of remote cerebellar hemorrhage (RCH) in patients with a dural tear duri...

Automated deep-neural-network surveillance of cranial images for acute neurologic events.

Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydroc...

Hybrid 3D/2D Convolutional Neural Network for Hemorrhage Evaluation on Head CT.

BACKGROUND AND PURPOSE: Convolutional neural networks are a powerful technology for image recognitio...

Predicting hospital admission at emergency department triage using machine learning.

OBJECTIVE: To predict hospital admission at the time of ED triage using patient history in addition ...

Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

A large recent study analyzed the relationship between multiple factors and neonatal outcome and in...

Artificial intelligence and machine learning in emergency medicine.

Interest in artificial intelligence (AI) research has grown rapidly over the past few years, in part...

Adverse Outcomes due to Aggressive Fluid Resuscitation in Children: A Prospective Observational Study.

Fluid management has a major impact on the duration, severity, and outcome of critically ill childre...

Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs...

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