AI Medical Compendium Journal:
CJEM

Showing 1 to 5 of 5 articles

Establishing methodological standards for the development of artificial intelligence-based Clinical Decision Support in emergency medicine.

CJEM
OBJECTIVE: Artificial intelligence (AI) offers opportunities for managing the complexities of clinical care in the emergency department (ED), and Clinical Decision Support has been identified as a priority application. However, there is a lack of pub...

Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care.

CJEM
STUDY OBJECTIVE: This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their predictive performance with the Canadian Triage Acuity Scale (CTAS) in identifying the need for critic...

Repeatability, reproducibility, and diagnostic accuracy of a commercial large language model (ChatGPT) to perform emergency department triage using the Canadian triage and acuity scale.

CJEM
PURPOSE: The release of the ChatGPT prototype to the public in November 2022 drastically reduced the barrier to using artificial intelligence by allowing easy access to a large language model with only a simple web interface. One situation where Chat...

A randomized trial of robot-based distraction to reduce children's distress and pain during intravenous insertion in the emergency department.

CJEM
OBJECTIVES: Our objectives were to evaluate the effectiveness of humanoid robot-based distraction on reducing distress and pain in children undergoing intravenous insertion.