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

Portela, Elaine Pinto; Cortes, Omar Andres Carmona; da Silva, Josenildo Costa

doi:10.1007/978-3-031-27440-4_10

Lecture Notes in Networks and Systems

2023

DOI: 10.1007/978-3-031-27440-4_10

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

Elaine Pinto Portela,

Omar Andres Carmona Cortes,

Josenildo Costa da Silva

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A rapid literature review on ensemble algorithms for COVID-19 classification using image-based exams

Portela,

Cortes,

da Silva

2023

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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. In this context, this review aims to answer four questions: (i) the most used ensemble technique, (ii) the accuracy those methods reached, (iii) the classes involved in the classification task, (iv) the main machine learning algorithms and models, and (v) the dataset used in the experiments.

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A rapid literature review on ensemble algorithms for COVID-19 classification using image-based exams

Portela,

Cortes,

da Silva

2023

HIS

View full text Add to dashboard Cite

show abstract

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

Cited by 1 publication

References 30 publications

A rapid literature review on ensemble algorithms for COVID-19 classification using image-based exams

A rapid literature review on ensemble algorithms for COVID-19 classification using image-based exams

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