Research Article
Modelling COVID-19 using Fuzzy Cognitive Maps (FCM)
@ARTICLE{10.4108/eai.24-2-2021.168728, author={Peter P. Groumpos}, title={Modelling COVID-19 using Fuzzy Cognitive Maps (FCM)}, journal={EAI Endorsed Transactions on Bioengineering and Bioinformatics}, volume={1}, number={2}, publisher={EAI}, journal_a={BEBI}, year={2021}, month={2}, keywords={COVID-19, medical diagnosis, modelling, fuzzy cognitive maps (FCM), artificial intelligence, advanced fuzzy cognitive maps (AFCM)}, doi={10.4108/eai.24-2-2021.168728} }- Peter P. Groumpos
Year: 2021
Modelling COVID-19 using Fuzzy Cognitive Maps (FCM)
BEBI
EAI
DOI: 10.4108/eai.24-2-2021.168728
Abstract
INTRODUCTION: The outbreak of COVID-19 has gained ground in many countries, leading towards a global health emergency. Research efforts have been intensified all around the humankind.
OBJECTIVE: The main objective of this paper is to study the new pandemic COVID-19 using for the first-time theories of Fuzzy Cognitive Maps (FCM).
METHODS: All known studies for COVID-19 are done based on statistical models. These statistical approaches depend solely on correlation factors. The factor of causality has not been considered due to the luck of sufficient mathematical models based on causality. Correlation does not imply causality while causality always implies correlation. The approach of Fuzzy Cognitive Maps (FCM) that is considering the causality factors is proposed, to investigate the whole spectrum of COVID-19.
RESULTS: Early theoretical simulation studies using a COVID-19 FCM model have been conducted. Simulations with real patient data give excellent results. The state space Advanced Fuzzy Cognitive Maps (AFCM) is the natural sequence of the classical FCM theories.
CONCLUSIONS: This study gives strong evidence that the “generic FCM theories” are probably the only ones that explore the causality between the variables of medical problems in a sound mathematical and scientific foundation.
Copyright © 2021 Peter P. Groumpos et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
