Related Experiment Video
Updated: Feb 7, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
Artificial intelligence and machine learning in emergency medicine
Jonathon Stewart1, Peter Sprivulis1, Girish Dwivedi1
1Royal Perth Hospital, Perth, Western Australia, Australia.
Abstract:
Interest in artificial intelligence (AI) research has grown rapidly over the past few years, in part thanks to the numerous successes of modern machine learning techniques such as deep learning, the availability of large datasets and improvements in computing power. AI is proving to be increasingly applicable to healthcare and there is a growing list of tasks where algorithms have matched or surpassed physician performance. Despite the successes there remain significant concerns and challenges surrounding algorithm opacity, trust and patient data security. Notwithstanding these challenges, AI technologies will likely become increasingly integrated into emergency medicine in the coming years. This perspective presents an overview of current AI research relevant to emergency medicine.
Related Concept Videos
Emerging Adulthood
Intelligence
Machines
A free-body diagram of the...
Measures of Intelligence
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
Introduction Cardiac Emergencies
Machines: Problem Solving II

