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Knowledge-based automatic performance evaluation for medical training debriefing
conference contribution
posted on 2014-01-01, 00:00 authored by James ZhangJames Zhang, Samer HanounSamer Hanoun, Douglas CreightonDouglas Creighton, Saeid Nahavandi, Karen D'SouzaKaren D'Souza, Kellie BrittKellie Britt, R YanieriManikin-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.
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Event
Systems, Man, and Cybernetics. Conference (2014 : San Diego, California)Pagination
2180 - 2185Publisher
IEEELocation
San Diego, CaliforniaPlace of publication
Piscataway, NJStart date
2014-10-05End date
2014-10-08ISBN-13
9781479938391Language
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2014, IEEEEditor/Contributor(s)
[Unknown]Title of proceedings
SMC 2014 : Proceedings of the 2014 IEEE International Conference on Systems, Man, and CyberneticsUsage metrics
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