{
  "id": 4362,
  "url": "https://arxiv.org/abs/2605.14113v2",
  "title": "ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows",
  "summary": "While interpretable prototype networks offer compelling case-based reasoning for clinical diagnostics, their raw continuous outputs lack the semantic structure required for medical documentation. Bridging this gap via standard Retrieval-Augmented Generation (RAG) routinely triggers ``retrieval sycophancy,'' where Large Language Models (LLMs) hallucinate post-hoc rationalizations to align with visual predictions. We introduce ProtoMedAgent, a framework that formalizes multimodal clinical reportin",
  "authors": "Alvaro Lopez Pellicer, Plamen Angelov, Marwan Bukhari, Yi Li, Eduardo Soares, Jemma Kerns",
  "category": "research",
  "topics": "safety-alignment,privacy-surveillance,healthcare,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-13T20:57:37.000Z",
  "fetched_at": "2026-07-14T16:30:54.924Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4362",
  "original_url": "https://arxiv.org/abs/2605.14113v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}