Fuzzy Decision Tree Based Method in Decision-Making of COVID-19 Patients’ Treatment

Jan Rabcan, Elena Zaitseva, Vitaly Levashenko, Miroslav Kvassay, Pavol Surda and Denisa Macekova
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Jan Rabcan: Department of Informatics, University of Žilina, Univerzitná 8215/1, 01026 Žilina, Slovakia
Elena Zaitseva: Department of Informatics, University of Žilina, Univerzitná 8215/1, 01026 Žilina, Slovakia
Vitaly Levashenko: Department of Informatics, University of Žilina, Univerzitná 8215/1, 01026 Žilina, Slovakia
Miroslav Kvassay: Department of Informatics, University of Žilina, Univerzitná 8215/1, 01026 Žilina, Slovakia
Pavol Surda: Department of Otolaryngology and Head and Neck Surgery, Guy’s & St, Thomas’ NHS Foundation Trust, Great Maze Pond, London SE1 9RT, UK
Denisa Macekova: Department of Informatics, University of Žilina, Univerzitná 8215/1, 01026 Žilina, Slovakia

Mathematics, 2021, vol. 9, issue 24, 1-16

Abstract: A new method in decision-making of timing of tracheostomy in COVID-19 patients is developed and discussed in this paper. Tracheostomy is performed in critically ill coronavirus disease (COVID-19) patients. The timing of tracheostomy is important for anticipated prolonged ventilatory wean when levels of respiratory support were favorable. The analysis of this timing has been implemented based on classification method. One of principal conditions for the developed classifiers in decision-making of timing of tracheostomy in COVID-19 patients was a good interpretation of result. Therefore, the proposed classifiers have been developed as decision tree based because these classifiers have very good interpretability of result. The possible uncertainty of initial data has been considered by the application of fuzzy classifiers. Two fuzzy classifiers as Fuzzy Decision Tree (FDT) and Fuzzy Random Forest (FRF) have been developed for the decision-making in tracheostomy timing. The evaluation of proposed classifiers and their comparison with other show the efficiency of the proposed classifiers. FDT has best characteristics in comparison with other classifiers.

Keywords: classification; prediction; fuzzy decision tree (FDT) and fuzzy random forest (FRF); COVID-19; tracheostomy (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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