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Validating Automatic Concept-Based Explanations for AI-Based Digital Histopathology
2022
Sensors
Digital histopathology poses several challenges such as label noise, class imbalance, limited availability of labelled data, and several latent biases to deep learning, negatively influencing transparency, reproducibility, and classification performance. In particular, biases are well known to cause poor generalization. Proposed tools from explainable artificial intelligence (XAI), bias detection, and bias discovery suffer from technical challenges, complexity, unintuitive usage, inherent
doi:10.3390/s22145346
pmid:35891026
pmcid:PMC9319808
fatcat:76cq4humgre6dlcuh67wsjlh2y