RETRACTED: Diagnosis of COVID-19 through blood sample using ensemble genetic algorithms and machine learning classifier
ISSN: 1708-5284
Article publication date: 1 July 2021
Issue publication date: 15 March 2022
Retraction statement
The publishers of World Journal of Engineering wish to retract the article Doewes, R.I., Nair, R. and Sharma, T. (2022), “Diagnosis of COVID-19 through blood sample using ensemble genetic algorithms and machine learning classifier”, World Journal of Engineering, Vol. 19 No. 2, pp. 175-182. https://doi.org/10.1108/WJE-03-2021-0174
An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald's publishing ethics and the COPE guidelines on retractions. The authors of this article would like to note that they do not agree with the content of this notice.
The publishers of the journal sincerely apologize to the readers.
Abstract
Purpose
This purpose of this study is to perfrom the analysis of COVID-19 with the help of blood samples. The blood samples used in the study consist of more than 100 features. So to process high dimensional data, feature reduction has been performed by using the genetic algorithm.
Design/methodology/approach
In this study, the authors will implement the genetic algorithm for the prediction of COVID-19 from the blood test sample. The sample contains records of around 5,644 patients with 111 attributes. The genetic algorithm such as relief with ant colony optimization algorithm will be used for dimensionality reduction approach.
Findings
The implementation of this study is done through python programming language and the performance evaluation of the model is done through various parameters such as accuracy, sensitivity, specificity and area under curve (AUC).
Originality/value
The implemented model has achieved an accuracy of 98.7%, sensitivity of 96.76%, specificity of 98.80% and AUC of 92%. The results have shown that the implemented algorithm has performed better than other states of the art algorithms.
Keywords
Acknowledgements
The authors are very thankful to our colleagues for their encouragement and motivation to write and implement the proposed work. The author has not recieved any funding to complete this work.
Citation
Doewes, R.I., Nair, R. and Sharma, T. (2022), "RETRACTED: Diagnosis of COVID-19 through blood sample using ensemble genetic algorithms and machine learning classifier", World Journal of Engineering, Vol. 19 No. 2, pp. 175-182. https://doi.org/10.1108/WJE-03-2021-0174
Publisher
:Emerald Publishing Limited
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