| Title of paper:
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An application of the InterCriteria Analysis and clusterization approach over a burnout dataset
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| Author(s):
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| Sotir Sotirov
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| Prof. Asen Zlatarov University, 1 Prof. Yakimov str. Burgas-8010, Bulgaria
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| ssotirov@btu.bg
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| Valentin Stoyanov
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| Prof. Asen Zlatarov University, 1 Prof. Yakimov str. Burgas-8010, Bulgaria
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| drvstoyanov@abv.bg
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| Maciej Krawczak
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Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland
Warsaw School of Information Technology, ul. Newelska 6, 01-447, Warsaw, Poland
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| m.krawczak@wit.edu.pl
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| Evdokia Sotirova
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| Prof. Asen Zlatarov University, 1 Prof. Yakimov str. Burgas-8010, Bulgaria
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| esotirova@btu.bg
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| Simeon Ribagin
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Prof. Asen Zlatarov University, 1 Prof. Yakimov str. Burgas-8010, Bulgaria
Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
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| simribagin@gmail.com
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| Presented at:
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25th ICIFS, Sofia, 9—10 September 2022
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| Published in:
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Notes on Intuitionistic Fuzzy Sets, Volume 28 (2022), Number 3, pages 353–360
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| DOI:
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https://doi.org/10.7546/nifs.2022.28.3.353-360
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| Download:
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 PDF (901 Kb, File info)
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| Abstract:
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In this investigation the level of burnout among the medical employees was analyzed. Тhe InterCriteria Analysis (ICA) approach is used to find the dependences between different parameters characterizing the 139 medical employees from 6 medical centers. The aim is to analyze the correlations between the health indicators, by surveying with a developed questionnaire. The obtained data from the InterCriteria Analysis were clustered using an adaptive neural network.
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| Keywords:
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Burnout syndrome questionnaire, InterCriteria Analysis, Intuitionistic fuzzy sets, Self-organizing map.
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| AMS Classification:
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03E72
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| References:
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