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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

Towards a Keyword Extraction in Medical and Healthcare Education

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DOI: http://dx.doi.org/10.15439/2017F351

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 173176 ()

Full text

Abstract. Medical and healthcare study programmes cover various curricula consisting of many theoretically focused courses and clinical teaching training. Curriculum attributes usually contains thousands of requirements on the form of knowledge and skills which fully define a complete graduate profile. It is not humanly possible to go through the entire curriculum or to imagine how the individual courses, learning units, outcomes and branches of medicine are interrelated. This paper introduces an innovative analytical approach which helps to identify automatically the most frequent topics based on keyword extraction. Moreover, the transparent and clear web-based visualisation of achieved results is shown in practice.

References

  1. R. H. Ellaway, S. Albright, V. Smothers, T. Cameron, and T. Willett, “Curriculum inventory: Modeling, sharing and comparing medical education programs,” Med. Teach., vol. 36, no. 3, pp. 208–215, nor 2014.
  2. M. Komenda, “Towards a Framework for Medical Curriculum Mapping,” Doctoral thesis, Masaryk University, Faculty of Informatics, 2015.
  3. M. Komenda, M. Karolyi, A. Pokorná, M. Víta, and V. Kríž, “Automatic keyword extraction from medical and healthcare curriculum,” in Computer Science and Information Systems (FedCSIS), 2016 Federated Conference on, 2016, pp. 287–290.
  4. J. Ooms, “The OpenCPU System: Towards a Universal Interface for Scientific Computing through Separation of Concerns,” ArXiv14064806 Cs Stat, Jun. 2014.
  5. “Model View Controller(MVC) in PHP.” [Online]. Available: http://php-html.net/tutorials/model-view-controller-in-php/. [Accessed: 24-Mar-2011].
  6. Y. Matsuo and M. Ishizuka, “Keyword extraction from a single document using word co-occurrence statistical information,” Int. J. Artif. Intell. Tools, vol. 13, no. 01, pp. 157–169, 2004.
  7. A. I. R. L. Azevedo, “KDD, SEMMA and CRISP-DM: a parallel overview,” 2008.
  8. A. Deyasi, S. Mukherjee, P. Debnath, and A. K. Bhattacharjee, Computational Science and Engineering: Proceedings of the International Conference on Computational Science and Engineering (Beliaghata, Kolkata, India, 4-6 October 2016). CRC Press, 2016.