Cargando…
Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period
In this research article, we introduced an algorithm to evaluate COVID-19 patients admission in hospitals at source shortage period. Many researchers have expressed their conclusions from different perspectives on various factors such as spatial changes, climate risks, preparedness, blood type, age...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8028601/ https://www.ncbi.nlm.nih.gov/pubmed/33846668 http://dx.doi.org/10.1016/j.eswa.2021.114997 |
_version_ | 1783675982895382528 |
---|---|
author | Geetha, Selvaraj Narayanamoorthy, Samayan Manirathinam, Thangaraj Kang, Daekook |
author_facet | Geetha, Selvaraj Narayanamoorthy, Samayan Manirathinam, Thangaraj Kang, Daekook |
author_sort | Geetha, Selvaraj |
collection | PubMed |
description | In this research article, we introduced an algorithm to evaluate COVID-19 patients admission in hospitals at source shortage period. Many researchers have expressed their conclusions from different perspectives on various factors such as spatial changes, climate risks, preparedness, blood type, age and comorbidities that may be contributing to COVID-19 mortality rate. However, as the number of people coming to the hospital for COVID-19 treatment increases, the mortality rate is likely to increase due to the lack of medical facilities. In order to provide medical assistance in this situation, we need to consider not only the extent of the disease impact, but also other important factors. No method has yet been proposed to calculate the priority of patients taking into account all the factors. We have provided a solution to this in this research article. Based on eight key factors, we provide a way to determine priorities. In order to achieve the effectiveness and practicability of the proposed method, we studied individuals with different results on all factors. The sigmoid function helps to easily construct factors at different levels. In addition, the cobweb solution model allows us to see the potential of our proposed algorithm very clearly. Using the method we introduced, it is easier to sort high-risk individuals to low-risk individuals. This will make it easier to deal with problems that arise when the number of patients in hospitals continues to increase. It can reduce the mortality of COVID-19 patients. Medical professionals can be very helpful in making the best decisions. |
format | Online Article Text |
id | pubmed-8028601 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80286012021-04-08 Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period Geetha, Selvaraj Narayanamoorthy, Samayan Manirathinam, Thangaraj Kang, Daekook Expert Syst Appl Article In this research article, we introduced an algorithm to evaluate COVID-19 patients admission in hospitals at source shortage period. Many researchers have expressed their conclusions from different perspectives on various factors such as spatial changes, climate risks, preparedness, blood type, age and comorbidities that may be contributing to COVID-19 mortality rate. However, as the number of people coming to the hospital for COVID-19 treatment increases, the mortality rate is likely to increase due to the lack of medical facilities. In order to provide medical assistance in this situation, we need to consider not only the extent of the disease impact, but also other important factors. No method has yet been proposed to calculate the priority of patients taking into account all the factors. We have provided a solution to this in this research article. Based on eight key factors, we provide a way to determine priorities. In order to achieve the effectiveness and practicability of the proposed method, we studied individuals with different results on all factors. The sigmoid function helps to easily construct factors at different levels. In addition, the cobweb solution model allows us to see the potential of our proposed algorithm very clearly. Using the method we introduced, it is easier to sort high-risk individuals to low-risk individuals. This will make it easier to deal with problems that arise when the number of patients in hospitals continues to increase. It can reduce the mortality of COVID-19 patients. Medical professionals can be very helpful in making the best decisions. Elsevier Ltd. 2021-09-15 2021-04-08 /pmc/articles/PMC8028601/ /pubmed/33846668 http://dx.doi.org/10.1016/j.eswa.2021.114997 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Geetha, Selvaraj Narayanamoorthy, Samayan Manirathinam, Thangaraj Kang, Daekook Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period |
title | Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period |
title_full | Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period |
title_fullStr | Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period |
title_full_unstemmed | Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period |
title_short | Fuzzy case-based reasoning approach for finding COVID-19 patients priority in hospitals at source shortage period |
title_sort | fuzzy case-based reasoning approach for finding covid-19 patients priority in hospitals at source shortage period |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8028601/ https://www.ncbi.nlm.nih.gov/pubmed/33846668 http://dx.doi.org/10.1016/j.eswa.2021.114997 |
work_keys_str_mv | AT geethaselvaraj fuzzycasebasedreasoningapproachforfindingcovid19patientspriorityinhospitalsatsourceshortageperiod AT narayanamoorthysamayan fuzzycasebasedreasoningapproachforfindingcovid19patientspriorityinhospitalsatsourceshortageperiod AT manirathinamthangaraj fuzzycasebasedreasoningapproachforfindingcovid19patientspriorityinhospitalsatsourceshortageperiod AT kangdaekook fuzzycasebasedreasoningapproachforfindingcovid19patientspriorityinhospitalsatsourceshortageperiod |