Computational Intelligence Conceptions to Automated Diagnosis: Feature Grouping for Performance Improvement

Abstract The motivation of this work is to investigate two technological AI paths, evaluate the performance, and discuss the results. Using a covid-19 chest X-ray images databank, we address the two distinct experiments to this problem: (1) an investigation of feature extraction and classification u...

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Bibliographic Details
Published in:	Brazilian Archives of Biology and Technology Vol. 66
Main Authors:	Nascimento, Francisco Assis de Oliveira, Saraiva Junior, Raimundo Guimarães, Faria, Edilaine Gonçalves Costa de, Silva, Tony Alexandre Medeiros da, Carvalho, João Luiz Azevedo de
Format:	Journal Article
Language:	English
Published:	Instituto de Tecnologia do Paraná (Tecpar) 01-01-2023
Subjects:	convolutional neural network covid-19 feature extraction machine learning transfer learning
Online Access:	Get full text
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Summary:	Abstract The motivation of this work is to investigate two technological AI paths, evaluate the performance, and discuss the results. Using a covid-19 chest X-ray images databank, we address the two distinct experiments to this problem: (1) an investigation of feature extraction and classification using machine learning algorithms and (2) an approach based on transfer learning used in state-of-the-art applications. For the implementation of our proposal (1), an integrated framework consisting of 25 algorithms with different characteristics was developed to extract features from chest X-ray images. Following this path, we seek to focus on the spatial spectral signatures of shape, texture, local and global statistical quantities. The extraction of features based on information in Fourier and wavelet space-frequency domain was also implemented as part of the framework. On the other hand, several transfer learning CNN’s were also used to evaluate performance and to compere to the first technological path results. Furthermore, the performance of other results reported by various other works are provided. The comparative performance evaluation demonstrated that the two concepts for a computational intelligence tool can produce very good results even working in high-dimensional vector spaces.
ISSN:	1516-8913 1678-4324
DOI:	10.1590/1678-4324-2023230609