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Intelligent Decision Support in a Nursing Educational Institution

Received: 6 February 2013    Accepted:     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), 2024. 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.
Cite This Article
  • 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
    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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Author Information
  • Faculty of Electrical Engineering, University of Maribor, Maribor, Slovenia; Faculty of Health Sciences, University of Maribor, Maribor, Slovenia

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