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. 2022;28(4):1223-1237.
doi: 10.1007/s00530-021-00774-w. Epub 2021 Mar 28.

Classification of COVID-19 individuals using adaptive neuro-fuzzy inference system

Celestine Iwendi  1 , Kainaat Mahboob  2 , Zarnab Khalid  2 , Abdul Rehman Javed  3 , Muhammad Rizwan  2 , Uttam Ghosh  4
Affiliations

Classification of COVID-19 individuals using adaptive neuro-fuzzy inference system

Celestine Iwendi et al. Multimed Syst. 2022.

Abstract

Coronavirus is a fatal disease that affects mammals and birds. Usually, this virus spreads in humans through aerial precipitation of any fluid secreted from the infected entity's body part. This type of virus is fatal than other unpremeditated viruses. Meanwhile, another class of coronavirus was developed in December 2019, named Novel Coronavirus (2019-nCoV), first seen in Wuhan, China. From January 23, 2020, the number of affected individuals from this virus rapidly increased in Wuhan and other countries. This research proposes a system for classifying and analyzing the predictions obtained from symptoms of this virus. The proposed system aims to determine those attributes that help in the early detection of Coronavirus Disease (COVID-19) using the Adaptive Neuro-Fuzzy Inference System (ANFIS). This work computes the accuracy of different machine learning classifiers and selects the best classifier for COVID-19 detection based on comparative analysis. ANFIS is used to model and control ill-defined and uncertain systems to predict this globally spread disease's risk factor. COVID-19 dataset is classified using Support Vector Machine (SVM) because it achieved the highest accuracy of 100% among all classifiers. Furthermore, the ANFIS model is implemented on this classified dataset, which results in an 80% risk prediction for COVID-19.

Keywords: ANFIS; COVID-19; Detection; Machine learning; Risk prediction; SVM.

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Figures

Fig. 1
Fig. 1
Proposed System for COVID-19 Risk Prediction
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Confusion matrix of complex DT classifier
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ROC Curve for complex DT
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Confusion matrix of fine KNN classifier
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ROC curve for fine KNN classifier
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Confusion matrix of linear SVM classifier
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ROC Curve for linear SVM classifier
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Sugeno FIS model
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ANFIS predictive model
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Sugeno model showing input and output
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Membership function of temperature associating inputs with outputs
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Fuzzy rule base of risk predictor
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Training data of proposed solution
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Testing of proposed solution
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Surface viewer of risk test
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ANFIS structure of risk prediction
See this image and copyright information in PMC

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