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MCRDR knowledge-based 3D dialogue simulation in clinical training and assessment

Citation

Yang, W and Herbert, D and Kim, S and Kang, B, MCRDR knowledge-based 3D dialogue simulation in clinical training and assessment, Journal of Medical Systems, 43 Article 200. ISSN 0148-5598 (2019) [Refereed Article]


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DOI: doi:10.1007/s10916-019-1262-0

Abstract

Dialogue-based simulation is a real-world practice technique for medical and clinical education that provides students with an opportunity to train using hands-on experiences without putting actual patients being put at risk. In this paper, a 3D interactive dialogue-based training and assessment system that supports the detailed development of clinical trial competency for medical students in a distributed virtual environment was proposed. For clinical training, MCRDR-based natural language understanding to realize the semantic representation of written dialog from the most relevant inference results was applied, and on the basis of this, a convolutional neural network model was also used to make the generated inference more exact and reliable. For clinical assessment, the dialogue-driven competency method was used to encompass medical knowledge, communication skill as well as professionalism skill based on the collected dialogue information. Finally, the potential of the created system was demonstrated with several clinical cases. The preliminary results indicate that the system demonstrates the potential of providing efficient training and flexible assessment, while saving time, improving practical skills and making students more confident.

Item Details

Item Type:Refereed Article
Keywords:dialogue simulation, MCRDR, knowledge base, competency assessment, clinical training
Research Division:Information and Computing Sciences
Research Group:Library and Information Studies
Research Field:Health Informatics
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Information Processing Services (incl. Data Entry and Capture)
UTAS Author:Yang, W (Ms Wenli Yang)
UTAS Author:Herbert, D (Mr David Herbert)
UTAS Author:Kim, S (Ms Sunny Kim)
UTAS Author:Kang, B (Professor Byeong Kang)
ID Code:137270
Year Published:2019
Deposited By:Information and Communication Technology
Deposited On:2020-02-06
Last Modified:2020-05-18
Downloads:0

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