Towards Interpretable, Sequential Multiple Instance Learning: An Application to Clinical Imaging
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This work introduces the Sequential Multiple Instance Learning (SMIL) framework, addressing the challenge of interpreting sequential, variable-length sequences of medical images with a single diagnostic label. Diverging from traditional MIL approaches that tre... ...
