A fuzzy rule-based efficient hospital bed management approach for coronavirus disease-19 infected patients

Kalyan Kumar Jena, Sourav Kumar Bhoi, Mukesh Prasad, Deepak Puthal

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Coronavirus disease-19 (COVID-19) is a very dangerous infectious disease for the entire world in the current scenario. Coronavirus spreads from one person to another person very rapidly. It spreads exponentially throughout the globe. Everyone should be cautious to avoid the spreading of this novel disease. In this paper, a fuzzy rule-based approach using priority-based method is proposed for the management of hospital beds for COVID-19 infected patients in the worst-case scenario where the number of hospital beds is very less as compared to the number of COVID-19 infected patients. This approach mainly attempts to minimize the number of hospital beds as well as emergency beds requirement for the treatment of COVID-19 infected patients to handle such a critical situation. In this work, higher priority has given to severe COVID-19 infected patients as compared to mild COVID-19 infected patients to handle this critical situation so that the survival probability of the COVID-19 infected patients can be increased. The proposed method is compared with first-come first-serve (FCFS)-based method to analyze the practical problems that arise during the assignment of hospital beds and emergency beds for the treatment of COVID-19 patients. The simulation of this work is carried out using MATLAB R2015b.

Original languageBritish English
Pages (from-to)11361-11382
Number of pages22
JournalNeural Computing and Applications
Volume34
Issue number14
DOIs
StatePublished - Jul 2022

Keywords

  • Coronavirus
  • COVID-19
  • FCFS-based method
  • Fuzzy rule-based approach
  • Hospital bed management
  • Priority-based method

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