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Fig. 3 | BMC Cancer

Fig. 3

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

Fig. 3

This diagram illustrates the process of identifying causal factors influencing the target variable from feature maps. The features depicted in the diagram can signify causes, effects of y, or maintain independence, as denoted by the arrows. Causal inference encompasses the examination of independence and conditional independence between y and attributes, thereby unveiling noteworthy causal factors

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BMC Cancer

ISSN: 1471-2407

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