Change in Normal Health Condition Due to COVID-19 Infection: Analysis by ANFIS Technique

The COVID-19 pandemic has crippled the world population. Our present work aims to formulate a model to analyze the change in normal health conditions due to COVID-19 infection. For this purpose, we have collected data of seven parameters, namely, age, systolic pressure (SP), diastolic paper (DP), re...

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Detalles Bibliográficos
Autores principales: Majumder, Rabindranath, Adak, Sayani, Jana, Soovoojeet, Patra, Sova, Kar, T. K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9463057/
https://www.ncbi.nlm.nih.gov/pubmed/36105072
http://dx.doi.org/10.1007/s40995-022-01344-z
Descripción
Sumario:The COVID-19 pandemic has crippled the world population. Our present work aims to formulate a model to analyze the change in normal health conditions due to COVID-19 infection. For this purpose, we have collected data of seven parameters, namely, age, systolic pressure (SP), diastolic paper (DP), respiratory distress (RD), fasting blood sugar (FBS), cholesterol (CHL), and insomnia (INS) of 156 persons of Birnagar municipality, Nadia, India; before and after COVID-19 infection. Ultimately, using an adaptive neuro-fuzzy inference system (ANFIS), we have formulated our desired model, a Takagi–Sugeno fuzzy inference system. Further, with the help of this model, we have established one’s change in health condition with age due to COVID-19 infection. Finally, we have derived that older people are more affected by COVID-19 infection than younger people.

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