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ENTITY Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study

Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study

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  1. RESEARCH · CL_167775 ·

    AI models lose critical cancer cues in mammography analysis · 2 papers

    Two new research papers explore the degradation of crucial diagnostic information in weakly supervised AI models used for mammography. The first paper introduces a gradient-based latent decomposition method to explain w…

  2. TOOL · CL_143836 ·

    New Calibratable Disambiguation Loss Improves AI Classifier Reliability

    Researchers have introduced a new method called Calibratable Disambiguation Loss (CDL) to improve the reliability of classifiers in Multi-Instance Partial-Label Learning (MIPL) tasks. This plug-and-play loss function en…

  3. RESEARCH · CL_90829 ·

    New Paper Reinterprets Image Classifiers as Multi-Instance Learners

    A new paper proposes a re-evaluation of global average pooling (GAP) in image classifiers, suggesting that these models can be interpreted as multi-instance learners. The research indicates that even when an image-level…