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Table 1.

Systematic literature review.

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Fig 1.

Proposed research flow diagram.

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Fig 2.

Sample medical images.

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Fig 3.

Proposed CNN architecture.

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Table 2.

Proposed Resnet50’s architecture.

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Fig 4.

Fitness function.

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Fig 5.

Image reconstruction.

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Fig 6.

Accuracy vs loss function (Red = Accuracy, Blue = Loss function).

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Fig 7.

Performance metrics.

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Table 3.

Performance analysis of proposed and other models.

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Table 4.

T-test for proposed and 2nd-best model (Enhanced residual network [63]).

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Fig 8.

Performance comparison of multi-classification with chest X-ray dataset.

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Table 5.

Chest X-ray dataset performance comparison with various existing models.

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Table 5 Expand

Fig 9.

Performance comparison of multi-classification with IDC dataset.

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Table 6.

IDC dataset performance comparison with various existing models.

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Table 6 Expand

Fig 10.

Performance comparison of multi-classification with COVID19-CT dataset.

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Table 7.

COVID19-CT dataset performance comparison with various existing models.

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Table 7 Expand

Fig 11.

Performance comparison of multi-classification with ISIC2018 dataset.

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Fig 11 Expand

Table 8.

ISIC2018 dataset performance comparison with various existing models.

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