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Published in: Annals of Data Science 4/2016

03-11-2016

Building Computational Virtual Reality Environment for Anesthesia

Authors: Wen Xu, Jinyuan He, Xinyu Cao, Peng Zhang, Wei Gao, Di Pan, Yingting Guo, Jing He

Published in: Annals of Data Science | Issue 4/2016

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Abstract

Traditional anaesthesia training is considered as a time-consuming task since trainees are required to go through an extended period of knowledge learning and practice their skill in the supervision of experienced anaesthetists. In this paper, a Computational Virtual Reality Environment for Anesthesia (CVREA) is proposed, which can significantly improve the training and learning performance of trainee anaesthetists in an efficient way. Virtual reality, big data, data mining and machine learning techniques will be explored and applied in this system. CVREA consists of two main parts: (1) an immersive and interactive VR-based training platform for anaesthetists. It allows trainees to hone their clinical skills in a virtual environment without placing risk to patients. (2) a knowledge learning system which records and collects clinical data with greater richness. Knowledge learning algorithms will be developed to explore these data in order to help data processing and facilitates knowledge discovery in anaesthesiology.

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Metadata
Title
Building Computational Virtual Reality Environment for Anesthesia
Authors
Wen Xu
Jinyuan He
Xinyu Cao
Peng Zhang
Wei Gao
Di Pan
Yingting Guo
Jing He
Publication date
03-11-2016
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 4/2016
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-016-0089-5

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