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

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.

3D Printed Face Shield as a Help for Nursing Homes during COVID-19 Pandemic

This paper describes the situation in Slovakia caused by the COVID-19 pandemic in 2020. The impact of lack of protective equipment by State Material Reserves motivated volunteers to help. While many individuals and organizations helped by sewing face masks and printing 3D face shields for hospital, our civic association- Slovak Python User Group- helped to design and print one thousand 3D face shields within two months. During these two months we have optimized all our 3D printers as well as the 3D models to increase production capacity. All face shields were sent to nursing homes in all regions of Slovakia. © 2021 IEEE.