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Table 9 The performance analysis of the presented methods using independence and conditional independence tests on the ShUCSEIT dataset

From: CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification—leveraging deep learning models for enhanced diagnostic accuracy

Models

Avg

Precision

Avg

Recall

Avg

F1-score

Avg

Accuracy

AUC

KNN

0.814

0.778

0.769

78.41%

0.865

SVM

0.897

0.896

0.894

89.09%

0.932

RF

0.851

0.852

0.851

85.00%

0.906

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BMC Cancer

ISSN: 1471-2407

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