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: Explaining the decision-making process of "black-box" Deep Learning (DL) models used in text classification , particularly within the biomedical domain.

: These models often require large datasets and can be sensitive to "adversarial noise" (small character-level changes that fool the AI). 113941

In this context, "deep text" refers to the application of techniques to Natural Language Processing (NLP) . : Explaining the decision-making process of "black-box" Deep

The identifier refers to a specific research article titled "Post-hoc explanation of black-box classifiers using confident itemsets" , published in the journal Expert Systems with Applications (Volume 165, March 2021). Key Details of the Research Authors : Milad Moradi and Matthias Samwald. The identifier refers to a specific research article

Post-hoc explanation of black-box classifiers using confident itemsets

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: Common architectures include Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) used to model complex relationships in text data.