Case2Flow: Bridging Patient Cases and Guideline Flowcharts through Multimodal Retrieval

• URL: http://arxiv.org/abs/2608.26414v1
• Date: Wed, 26 Aug 2026 21:27:22 GMT
• Title: Case2Flow: Bridging Patient Cases and Guideline Flowcharts through Multimodal Retrieval
• Abstract summary: Case2Flow is a task designed to retrieve the most relevant guideline flowchart for a given patient case.<n> FlowAtlas is a curated corpus of 202 flowcharts extracted from 2,080 medical guidelines.<n> CRISP is a training-free scoring method that sharpens late-interaction retrieval by suppressing uninformative patches.
• Score: 65.99409194536337
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Medical guidelines encode rich, evidence-based decision logic, yet the specific decision artifact a clinician needs is hard to locate within a guideline, let alone across guidelines covering plausible diseases and treatments. While guideline passages have supported end-to-end question answering, flowcharts remain largely underused in decision support despite their ability to encode actionable clinical pathways. We therefore introduce Case2Flow, a task designed to retrieve the most relevant guideline flowchart for a given patient case from a collection of guideline documents. To support it, we construct FlowAtlas, a curated corpus of 202 flowcharts extracted from 2,080 medical guidelines, together with a pipeline that synthesises 1,911 aligned case-flowchart pairs. Our evaluation of multimodal retrieval methods reveals systematic failure modes, including overreliance on keywords and spurious token-patch matches induced by uninformative background regions in flowcharts. Motivated by this, we propose CRISP, a training-free scoring method that sharpens late-interaction retrieval by suppressing uninformative patches, discounting ambiguous token matches, and incorporating bidirectional query-image alignment. CRISP improves Recall@1 by up to 18.71 percentage points, while a blinded physician assessment on published case narratives provides preliminary feasibility evidence beyond synthetic queries.

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