A new multiple instance learning model for whole-slide images produces inherently interpretable predictions by combining vision-language concept detection with a linear decision rule.
B-cos networks: Align- ment is all we need for interpretability
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Label-free Concept Based Multiple Instance Learning for Gigapixel Histopathology
A new multiple instance learning model for whole-slide images produces inherently interpretable predictions by combining vision-language concept detection with a linear decision rule.