AIMC Topic: Emergency Medicine

Clear Filters Showing 61 to 70 of 73 articles

Can Gpt-4o Accurately Diagnose Trauma X-Rays? A Comparative Study with Expert Evaluations.

The Journal of emergency medicine
BACKGROUND: The latest artificial intelligence (AI) model, GPT-4o, introduced by OpenAI, can process visual data, presenting a novel opportunity for radiographic evaluation in trauma patients.

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

Studies in health technology and informatics
Natural Language Processing (NLP) has shown promise in fields like radiology for converting unstructured into structured data, but acquiring suitable datasets poses several challenges, including privacy concerns. Specifically, we aim to utilize Large...

Comparison of the problem-solving performance of ChatGPT-3.5, ChatGPT-4, Bing Chat, and Bard for the Korean emergency medicine board examination question bank.

Medicine
Large language models (LLMs) have been deployed in diverse fields, and the potential for their application in medicine has been explored through numerous studies. This study aimed to evaluate and compare the performance of ChatGPT-3.5, ChatGPT-4, Bin...

Applications of Artificial Intelligence and Machine Learning in Emergency Medicine Triage - A Systematic Review.

Medical archives (Sarajevo, Bosnia and Herzegovina)
BACKGROUND: Overcrowding in Emergency departments adversely impacts efficiency, patient outcomes, and resource allocation. Accurate triage systems are essential for prioritizing care and optimizing resources. While traditional methods provide a found...

Transforming emergency triage: A preliminary, scenario-based cross-sectional study comparing artificial intelligence models and clinical expertise for enhanced accuracy.

Bratislavske lekarske listy
INTRODUCTION: This study examines triage judgments in emergency settings and compares the outcomes of artificial intelligence models for healthcare professionals. It discusses the disparities in precision rates between subjective evaluations by healt...