Building Computational Virtual Reality Environment for Anesthesia

Wen Xu, Jinyuan He (), Xinyu Cao, Peng Zhang, Wei Gao, Di Pan, Yingting Guo and Jing He
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Wen Xu: Nanjing University of Finance and Economic
Jinyuan He: Victoria University
Xinyu Cao: Victoria University
Peng Zhang: Victoria University
Wei Gao: Jiangsu Grain and Oil Information Center
Di Pan: Jiangsu Grain and Oil Information Center
Yingting Guo: Victoria University
Jing He: Nanjing University of Finance and Economic

Annals of Data Science, 2016, vol. 3, issue 4, No 4, 413-421

Abstract: 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.

Keywords: Anaesthesia; Virtual reality; Physiological data; Data mining; Machine learning; Big data (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s40745-016-0089-5

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