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Knowledge-based automatic performance evaluation for medical training debriefing

Version 2 2024-06-02, 13:21
Version 1 2015-04-17, 17:35
conference contribution
posted on 2024-06-02, 13:21 authored by James ZhangJames Zhang, Samer HanounSamer Hanoun, Douglas CreightonDouglas Creighton, S Nahavandi, Karen D'SouzaKaren D'Souza, Kellie BrittKellie Britt, R Yanieri
Manikin-based medical simulation has been shown to benefit the knowledge, skills and attitudes of the learner, and to impart favourable patient effects. A vital component of any training simulation is the after-session discussion with trainees to debrief their performance. In this study we develop a rule-based debriefing tool for improving the efficacy of medical training sessions. Unlike most existing de-briefing tools, the tool presented here has been designed to reduce medical trainer assessment time and to improve evaluation accuracy through a largely automated evaluation of trainee performance. The developed tool is acknowledged by the School of Medicine of Deakin University as an important advancement in assisting medical trainers carry out the debriefing process effectively and efficiently.

History

Pagination

2180-2185

Location

San Diego, California

Start date

2014-10-05

End date

2014-10-08

ISBN-13

9781479938391

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2014, IEEE

Editor/Contributor(s)

[Unknown]

Title of proceedings

SMC 2014 : Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics

Event

Systems, Man, and Cybernetics. Conference (2014 : San Diego, California)

Publisher

IEEE

Place of publication

Piscataway, NJ

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