Proceedings of the 2015 International conference on Engineering Management, Engineering Education and Information Technology

Application of Classification Methods to Elective Surgical Cases Cancellation Detection

Authors
Li Feng, Li Luo, Renrong Gong
Corresponding Author
Li Feng
Available Online November 2015.
DOI
https://doi.org/10.2991/emeeit-15.2015.60How to use a DOI?
Keywords
Surgery Cancellation, Operating Room Management, Decision Tree, Bayes Network, Classification Techniques
Abstract

The case cancellation in the operating room can cause multi-faceted troubles, so it is difficult for the operating room manager to detect potential cancelled cases. The objective of this study is to build classification models like Decision Tree and Bayes Network to assist the operating room manager to detect the potential cancelled cases. After data acquisition and data preprocessing, classification models are trained. As a result, Decision Tree and Bayes Network outperform SVM and Neural Networks in terms of classification accuracy.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Engineering Management, Engineering Education and Information Technology
Series
Advances in Computer Science Research
Publication Date
November 2015
ISBN
978-94-6252-121-6
ISSN
2352-538X
DOI
https://doi.org/10.2991/emeeit-15.2015.60How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Li Feng
AU  - Li Luo
AU  - Renrong Gong
PY  - 2015/11
DA  - 2015/11
TI  - Application of Classification Methods to Elective Surgical Cases Cancellation Detection
BT  - Proceedings of the 2015 International conference on Engineering Management, Engineering Education and Information Technology
PB  - Atlantis Press
SP  - 298
EP  - 302
SN  - 2352-538X
UR  - https://doi.org/10.2991/emeeit-15.2015.60
DO  - https://doi.org/10.2991/emeeit-15.2015.60
ID  - Feng2015/11
ER  -