Emergency Medicine

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

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Showing 2584-2604 of 5,260 articles
Construction of a predictive model for rebleeding risk in upper gastrointestinal bleeding patients based on clinical indicators such as infection.

BACKGROUND: The annual incidence of upper gastrointestinal hemorrhage (UGIB) is about 60 cases/100,0...

Deployable machine learning-based decision support system for tracheostomy in acute burn patients.

BACKGROUND: Airway obstruction is a common emergency in acute burns with high mortality. Tracheostom...

Performance analysis of an emergency triage system in ophthalmology using a customized CHATBOT.

PURPOSE: To evaluate the performance of a custom ChatGPT-based chatbot in triaging ophthalmic emerge...

A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration.

INTRODUCTION: Medical device recalls are important to the practice of emergency medicine, as unsafe ...

A Novel Ensemble Approach for Rib Fracture Detection and Visualization using CNNs and Grad-CAM.

AIM: This study aimed to develop a reliable and efficient system for predicting and locating rib fra...

Challenges and opportunities for validation of AI-based new approach methods.

The integration of artificial intelligence (AI) into new approach methods (NAMs) for toxicology rep-...

Is Generative AI Increasing the Risk for Technology-Mediated Trauma Among Vulnerable Populations?

The proliferation of Generative Artificial Intelligence (Generative AI) has led to an increased reli...

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdomi...

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans.

Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intram...

[Image reconstruction for cerebral hemorrhage based on improved densely-connected fully convolutional neural network].

Cerebral hemorrhage is a serious cerebrovascular disease with high morbidity and high mortality, for...

[Not Available].

Our purpose was to evaluate the approach of two different chatbots (ChatGPT and Gemini) to a list of...

[Application progress and future prospects of interventional robotics in vascular injury hemostasis].

The field of traumatic hemostasis is currently confronted with numerous challenges, particularly in ...

Generating Synthetic Healthcare Dialogues in Emergency Medicine Using Large Language Models.

Natural Language Processing (NLP) has shown promise in fields like radiology for converting unstruct...

Using Deep Learning to Suggest Treatment for Proximal Humerus Fractures.

Proximal humeral fractures are among the most common fractures seen in emergency departments. Accura...

Letter to Editor Regarding "Use of Artificial Intelligence Software to Detect Intracranial Aneurysms: A Comprehensive Stroke Center Experience".

Artificial intelligence (AI) is increasingly significant in neurosurgery, enhancing differential dia...

Care to Explain? AI Explanation Types Differentially Impact Chest Radiograph Diagnostic Performance and Physician Trust in AI.

Background It is unclear whether artificial intelligence (AI) explanations help or hurt radiologists...

Proactive care management of AI-identified at-risk patients decreases preventable admissions.

OBJECTIVES: We assessed whether proactive care management for artificial intelligence (AI)-identifie...

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