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

Rabindranath Majumder^1,2, Sayani Adak³, Soovoojeet Jana⁴

¹Department of Physiology, Tamralipta Mahavidyalaya, Tamluk, Purba Medinipur, West Bengal 721636 India.

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|September 15, 2022

Summary

This study models health changes after COVID-19 infection using an adaptive neuro-fuzzy inference system (ANFIS). Older individuals experienced more significant health detriments compared to younger ones.

Keywords:

ANFIS Age COVID-19 Normalized Health Condition (NHC)Subtractive algorithm

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Area of Science:

Health Sciences
Computational Biology
Epidemiology

Background:

The COVID-19 pandemic significantly impacted global health.
Assessing post-infection health changes is crucial for understanding long-term effects.
Individual health parameters can be altered by viral infections.

Purpose of the Study:

To develop a predictive model for analyzing health condition changes post-COVID-19 infection.
To investigate the relationship between age and COVID-19's impact on health.
To utilize the adaptive neuro-fuzzy inference system (ANFIS) for health data analysis.

Main Methods:

Data collection from 156 individuals in Nadia, India, before and after COVID-19 infection.
Inclusion of seven health parameters: age, systolic pressure (SP), diastolic pressure (DP), respiratory distress (RD), fasting blood sugar (FBS), cholesterol (CHL), and insomnia (INS).
Development of a Takagi-Sugeno fuzzy inference system model using ANFIS.

Main Results:

The ANFIS model successfully analyzed health changes attributed to COVID-19.
Established a correlation between age and the degree of health alteration post-infection.
Demonstrated that older individuals exhibited more pronounced negative health changes.

Conclusions:

The developed ANFIS model provides a framework for assessing COVID-19's health impact.
Age is a significant factor influencing the severity of health deterioration after COVID-19.
The study highlights the vulnerability of older populations to COVID-19-related health complications.