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Selecting the right image can boost dermatology model accuracy by an average of 20 percentage points, but existing methods struggle to close the gap to optimal performance.
Semantic equivalence measures can drastically change how we quantify annotator agreement in biomedical text, revealing hidden biases in existing methods.