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DISCERN: A Clinical Impact-aware Framework for Radiology Report Comparison

2026-05-27

Abstract excerpt

The surge in medical imaging has spurred the development of vision-language models (VLMs) to alleviate radiologist workloads. However, clinical deployment is hindered by the lack of meaningful evaluation frameworks. Current metrics - ranging from semantic similarity to large language model (LLM) based judges - often fail to distinguish between clinically trivial and critical discrepancies, poorly reflecting real-w...

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Literature Corpus work
c0c884d7-e58a-5ea4-966f-4de825bad6f6
DOI
10.64898/2026.05.26.26353612
Open publication

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Semantic proximity does not establish scientific evidence.

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DISCERN: A Clinical Impact-aware Framework for Radiology Report ComparisonDOI 10.64898/2026.05.26.26353612
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