Emergency Medicine

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

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Artificial Intelligence in Spine Imaging: A Paradigm Shift in Diagnosis and Care.

Recent advancements in artificial intelligence (AI) can significantly improve radiologists' workflow...

Machine Learning and Deep Learning Models for Automated Protocoling of Emergency Brain MRI Using Text from Clinical Referrals.

Purpose To develop and evaluate machine learning and deep learning-based models for automated protoc...

Editorial Commentary: Large Language Models Like ChatGPT Show Promise, but Clinical Use of Artificial Intelligence Requires Physician Partnership.

Forcing ChatGPT and other large language models to perform roles reserved for physicians and other h...

Evaluation of a BERT Natural Language Processing Model for Automating CT and MRI Triage and Protocol Selection.

To evaluate the accuracy of a Bidirectional Encoder Representations for Transformers (BERT) Natural...

Deep Learning Applications in Imaging of Acute Ischemic Stroke: A Systematic Review and Narrative Summary.

Background Acute ischemic stroke (AIS) is a major cause of morbidity and mortality, requiring swift ...

Generative AI and the profession of genetic counseling.

The development of artificial intelligence (AI) including generative large language models (LLMs) an...

Prehospital triage of trauma patients: predicting major surgery using artificial intelligence as decision support.

BACKGROUND: Matching the necessary resources and facilities to attend to the needs of trauma patient...

Machine Learning-Based Rapid Prediction of Torsional Performance of Personalized Peripheral Artery Stent.

The complex mechanical environment of peripheral arteries makes stents with poor torsional performan...

Applying Conformal Prediction to a Deep Learning Model for Intracranial Hemorrhage Detection to Improve Trustworthiness.

Purpose To apply conformal prediction to a deep learning (DL) model for intracranial hemorrhage (ICH...

Deep learning model for identifying acute heart failure patients using electrocardiography in the emergency room.

AIMS: Acute heart failure (AHF) poses significant diagnostic challenges in the emergency room (ER) b...

Detection and classification of glomerular lesions in kidney graft biopsies using 2-stage deep learning approach.

Acute allograft rejection in patients undergoing renal transplantation is diagnosed through histopat...

Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language Models.

Background Incomplete clinical histories are a well-known problem in radiology. Previous dedicated q...

Factors Contributing to Fatalities in Helicopter Emergency Medical Service Accidents.

INTRODUCTION: This study aimed to update and reinforce previous research on helicopter emergency med...

Scale to predict risk for refractory septic shock based on a hybrid approach using machine learning and regression modeling.

OBJECTIVE: To develop a scale to predict refractory septic shock (SS) based on clinical variables re...

Artificial Intelligence-Based Early Prediction of Acute Respiratory Failure in the Emergency Department Using Biosignal and Clinical Data.

PURPOSE: Early identification of patients at risk for acute respiratory failure (ARF) could help cli...

Potential Impact of an Artificial Intelligence-based Mammography Triage Algorithm on Performance and Workload in a Population-based Screening Sample.

OBJECTIVE: To evaluate potential screening mammography performance and workload impact using a comme...

Motion-Mimicking Robotic Finger Prosthesis for Burn-induced Partial Hand Amputee: A Case Report.

Burn injuries often result in severe hand complications, including joint contractures and nerve dama...

Comparing Artificial Intelligence Guided Image Assessment to Current Methods of Burn Assessment.

Appropriate identification of burn depth and size is paramount. Despite the development of burn dept...

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