Intelligent Decision Support in a Nursing Educational Institution

Peter Kokol

doi:doi:10.11648/j.ajns.20130202.11

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Intelligent Decision Support in a Nursing Educational Institution

Peter Kokol

Published in American Journal of Nursing Science (Volume 2, Issue 2)

Published: 2 April 2013

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Abstract

Evidence-based management is defined as a process of translating best evidence into organizational management practices. Surprisingly only 15 percent of decisions are evidence based. In the paper we present the idea how intelligent systems can be used to improve the current situation and show in a case study how intelligent systems can be successfully used to extract evidence to improve management practices and decision making, especially in human resource management.

Published in	American Journal of Nursing Science (Volume 2, Issue 2)
DOI	10.11648/j.ajns.20130202.11
Page(s)	14-17
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Evidence Based Practice, Evidence Based Management, Decision Making, Intelligent Systems

References

[1]	Bakken, S./McArthur, J. (2001): Evidence-based nursing practice: A call to action for nursing informatics, in: Journal of The American Medical Informatics Association, 8, 3, 289-290.
[2]	Breiman, L./Friedman, J.H./Olshen, R.A./Stone, C.J. (1984): Classification and regression trees. Monterey, CA: Wadsworth, Inc.
[3]	Dietterich, T.G. (2001): Ensemble methods in machine learning, in: Kittler, J., Roli, F. (eds.): Multiple Classifier Systems, LNCS Vol. 1857, Springer, 1–15.
[4]	Murthy, S.K. (1998): Automatic construction of decision trees from data: A multi-disciplinary survey, in: Data Mining and Knowledge Discovery 2, 345-389.
[5]	Pffefer, J., Sutton R.I. (2001), "Evidence Based Management", Harward Business Review, jan 2008.
[6]	Quinlan, J.R.: Induction of decision trees, in: Machine learning, 1.
[7]	Rynes S./Giluk T.L./Browm K.G. (2007): The very separate worlds of academia and practitioner periodicals in human resource management: Implications for evidence based management, in: Academy of Management Journal, 50, 5, 987–1008.
[8]	Schapire R.E. (1990): The strength of weak learnability, in: Machine Learning, 5, 2, 197-227.
[9]	Witten, I.H./Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann Series in Data Management Systems, Morgan Kaufmann.
[10]	Freund Y./Mason L. (1999): The Alternating Decision Tree Algorithm, in: Proceedings of the 16th International Confe-rence on Machine Learning, 124-133.

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APA Style

Peter Kokol. (2013). Intelligent Decision Support in a Nursing Educational Institution. American Journal of Nursing Science, 2(2), 14-17. https://doi.org/10.11648/j.ajns.20130202.11

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ACS Style

Peter Kokol. Intelligent Decision Support in a Nursing Educational Institution. Am. J. Nurs. Sci. 2013, 2(2), 14-17. doi: 10.11648/j.ajns.20130202.11

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AMA Style

Peter Kokol. Intelligent Decision Support in a Nursing Educational Institution. Am J Nurs Sci. 2013;2(2):14-17. doi: 10.11648/j.ajns.20130202.11

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@article{10.11648/j.ajns.20130202.11,
  author = {Peter Kokol},
  title = {Intelligent Decision Support in a Nursing Educational Institution},
  journal = {American Journal of Nursing Science},
  volume = {2},
  number = {2},
  pages = {14-17},
  doi = {10.11648/j.ajns.20130202.11},
  url = {https://doi.org/10.11648/j.ajns.20130202.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajns.20130202.11},
  abstract = {Evidence-based management is defined as a process of translating best evidence into organizational management practices. Surprisingly only 15 percent of decisions are evidence based. In the paper we present the idea how intelligent systems can be used to improve the current situation and show in a case study how intelligent systems can be successfully used to extract evidence to improve management practices and decision making, especially in human resource management.},
 year = {2013}
}

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TY  - JOUR
T1  - Intelligent Decision Support in a Nursing Educational Institution
AU  - Peter Kokol
Y1  - 2013/04/02
PY  - 2013
N1  - https://doi.org/10.11648/j.ajns.20130202.11
DO  - 10.11648/j.ajns.20130202.11
T2  - American Journal of Nursing Science
JF  - American Journal of Nursing Science
JO  - American Journal of Nursing Science
SP  - 14
EP  - 17
PB  - Science Publishing Group
SN  - 2328-5753
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AB  - Evidence-based management is defined as a process of translating best evidence into organizational management practices. Surprisingly only 15 percent of decisions are evidence based. In the paper we present the idea how intelligent systems can be used to improve the current situation and show in a case study how intelligent systems can be successfully used to extract evidence to improve management practices and decision making, especially in human resource management.
VL  - 2
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Author Information

Peter Kokol

Faculty of Electrical Engineering, University of Maribor, Maribor, Slovenia

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Plain Text BibTeX RIS

APA Style

Peter Kokol. (2013). Intelligent Decision Support in a Nursing Educational Institution. American Journal of Nursing Science, 2(2), 14-17. https://doi.org/10.11648/j.ajns.20130202.11

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ACS Style

Peter Kokol. Intelligent Decision Support in a Nursing Educational Institution. Am. J. Nurs. Sci. 2013, 2(2), 14-17. doi: 10.11648/j.ajns.20130202.11

Copy | Download

AMA Style

Peter Kokol. Intelligent Decision Support in a Nursing Educational Institution. Am J Nurs Sci. 2013;2(2):14-17. doi: 10.11648/j.ajns.20130202.11

Copy | Download

@article{10.11648/j.ajns.20130202.11,
  author = {Peter Kokol},
  title = {Intelligent Decision Support in a Nursing Educational Institution},
  journal = {American Journal of Nursing Science},
  volume = {2},
  number = {2},
  pages = {14-17},
  doi = {10.11648/j.ajns.20130202.11},
  url = {https://doi.org/10.11648/j.ajns.20130202.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajns.20130202.11},
  abstract = {Evidence-based management is defined as a process of translating best evidence into organizational management practices. Surprisingly only 15 percent of decisions are evidence based. In the paper we present the idea how intelligent systems can be used to improve the current situation and show in a case study how intelligent systems can be successfully used to extract evidence to improve management practices and decision making, especially in human resource management.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Intelligent Decision Support in a Nursing Educational Institution
AU  - Peter Kokol
Y1  - 2013/04/02
PY  - 2013
N1  - https://doi.org/10.11648/j.ajns.20130202.11
DO  - 10.11648/j.ajns.20130202.11
T2  - American Journal of Nursing Science
JF  - American Journal of Nursing Science
JO  - American Journal of Nursing Science
SP  - 14
EP  - 17
PB  - Science Publishing Group
SN  - 2328-5753
UR  - https://doi.org/10.11648/j.ajns.20130202.11
AB  - Evidence-based management is defined as a process of translating best evidence into organizational management practices. Surprisingly only 15 percent of decisions are evidence based. In the paper we present the idea how intelligent systems can be used to improve the current situation and show in a case study how intelligent systems can be successfully used to extract evidence to improve management practices and decision making, especially in human resource management.
VL  - 2
IS  - 2
ER  -

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