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arXiv Computation and Language By Junda Wang, Zonghai Yao, Yujan Ting, Eric Z. Chen, Hieu Tran, Hong Yu, Weijing Huang, Terrence Chen

MultiViewDx: Evidence-Linked Multi-View Clinical Diagnosis

Read the original on arXiv Computation and Language →

MultiViewDx is a physician‑validated multimodal instruction dataset that links medical imaging studies with patient context and normalizes heterogeneous reports into an evidence‑linked workflow (evidence → findings → differential discussion → diagnosis). The dataset covers a wide range of imaging modalities and uses a unified image‑text retriever to ensure that instruction synthesis is grounded in source‑supported evidence. Fine‑tuned models on MultiViewDx achieve the highest average accuracy on four MedVQA benchmarks and receive the strongest overall rating on JAMA Clinical Challenge cases, with ablations confirming the importance of case‑level multi‑view organization and evidence‑linked reasoning.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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