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A Rapid Review on Ensemble Algorithms for COVID-19 Classification Using Image-Based Exams

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Intelligent Systems Design and Applications (ISDA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 646))

Abstract

The world recently has faced the COVID-19 pandemic, a disease caused by the severe acute respiratory syndrome. The main features of this disease are the rapid spread and high-level mortality. The illness led to the rapid development of a vaccine that we know can fight against the virus; however, we do not know the actual vaccine’s effectiveness. Thus, the early detection of the disease is still necessary to provide a suitable course of action. To help with early detection, intelligent methods such as machine learning and computational intelligence associated with computer vision algorithms can be used in a fast and efficient classification process, especially using ensemble methods that present similar efficiency to traditional machine learning algorithms in the worst-case scenario. Therefore, this review is relevant for driving researchers interested in investigating ensemble methods to improve the classification quality of their algorithms and avoid duplicated efforts.

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Authors and Affiliations

  1. Programa de Pós-Graduação em Engenharia da Computação (PECS), Universidade Estadual do Maranhão (UEMA), São Luis, MA, Brazil

    Elaine Pinto Portela

  2. Departamento de Computação (DCOMP), Instituto Federal do Maranhão (IFMA), São Luis, MA, Brazil

    Omar Andres Carmona Cortes & Josenildo Costa da Silva

Authors
  1. Elaine Pinto Portela
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  2. Omar Andres Carmona Cortes
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  3. Josenildo Costa da Silva
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Corresponding author

Correspondence to Omar Andres Carmona Cortes .

Editor information

Editors and Affiliations

  1. Faculty of Computing and Data Science, FLAME University, Pune, Maharashtra, India

    Ajith Abraham

  2. Center for Smart Computing Continuum, Burgenland, Austria

    Sabri Pllana

  3. University of Bari, Bari, Italy

    Gabriella Casalino

  4. University of Jinan, Jinan, Shandong, China

    Kun Ma

  5. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Anu Bajaj

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Portela, E.P., Cortes, O.A.C., da Silva, J.C. (2023). A Rapid Review on Ensemble Algorithms for COVID-19 Classification Using Image-Based Exams. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 646. Springer, Cham. https://doi.org/10.1007/978-3-031-27440-4_10

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