ISCRAM Digital Library -- Query Results

	ISCRAM Digital Library Home \| Show All \| Simple Search \| Advanced Search	Login Quick Search: Field: contains: ...
	1–1 of 1 record found matching your query (RSS):

Search & Display Options

Select All Deselect All

<< 1 >>

|

|

Details

	Record						Links
	Author	Peng Xia; Ji Ruan; Dave Parry; Jian Yu; Sally Britnell
	Title	Enhancing Triage Training for Mass Casualty Incidents with Virtual Reality and Artificial Intelligence			Type	Conference Article
	Year	2023	Publication	Proceedings of the ISCRAM Asia Pacific Conference 2022	Abbreviated Journal	Proc. ISCRAM AP 2022
	Volume		Issue		Pages	68-76
	Keywords	Mass Casualty Incidents; Triage Training; Virtual Reality; Artificial Intelligence
	Abstract	Mass casualty incidents (MCIs) occur with natural or man-made disasters. Training emergency staff for combating MCIs is essential, but the cost can be high as such incidents rarely occur, and a physical simulation is resource-intensive. Triage is a critical task in dealing with MCIs. In this paper, we propose to use Virtual Reality (VR) and Artificial Intelligence (AI) technologies to build a low-cost, high-efficient system for MCI triage training. Our system captures more comprehensive training data and utilizes state-of-the-art AI evaluation methods.
	Address	Auckland University of Technology; Auckland University of Technology; Murdoch University; Auckland Unviversity of Technology; Auckland University of Technology
	Corporate Author				Thesis
	Publisher	Massey Unversity	Place of Publication	Palmerston North, New Zealand	Editor	Thomas J. Huggins, V.L.
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Track	Practitioners Track	Expedition		Conference
	Notes				Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2481
Share this record to Facebook

Select All Deselect All

<< 1 >>

|

|

Details

All Found Records Selected Records:

Save Citations: Format:

Export Records: Format:

CQL Search | Library Search | Show Record | Extract Citations