Papers with multi-class settings

    1 papers
    EnSidNet: Enhanced Hybrid Siamese-Deep Network for grouping clinical trials into drug-development pathways (2021.naacl-main)

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    Challenge: Siamese Neural Networks have been widely used to perform similarity classification in multi-class settings.
    Approach: They propose an Enhanced hybrid Siamese-Deep Neural Network (EnSidNet) that can be used to group clinical trials belonging to the same drug-development pathway along the several clinical trial phases.
    Outcome: The proposed model shows significant improvement above baselines in a 1-shot evaluation setting and in . a classical similarity setting.

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