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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.
Afiliación
  • Geetha S; Department of Mathematics, Bharathiar University, Coimbatore 641046, TamilNadu, India.
  • Narayanamoorthy S; Department of Mathematics, Bharathiar University, Coimbatore 641046, TamilNadu, India.
  • Manirathinam T; Department of Mathematics, Bharathiar University, Coimbatore 641046, TamilNadu, India.
  • Kang D; Department of Industrial and Management Engineering, Institute of Digital Anti-aging Health care, Inje University, 197, Inje-ro, Gimhae-si, Gyeongsangnam-do, Republic of Korea.
Expert Syst Appl ; 178: 114997, 2021 Sep 15.
Article en En | MEDLINE | ID: mdl-33846668
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Expert Syst Appl Año: 2021 Tipo del documento: Article País de afiliación: India Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Expert Syst Appl Año: 2021 Tipo del documento: Article País de afiliación: India Pais de publicación: Estados Unidos