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Model-agnostic Knowledge Augmented Machine Learning for Weakly Annotated Bioimaging Data
Machine learning models are increasingly used for automated feature extraction from weakly annotated bioimaging data, such as microscopy and cytomorphology images. Due to the sole dependency of automated feature extraction, existing methods yield inconsistent classification performance across weakly
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