@inproceedings{liao-etal-2026-diagnosing,
    title = "Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic {LLM}s",
    author = "Liao, Zicen  and
      Sun, Yunhao  and
      Purver, Matthew",
    editor = "Demner-Fushman, Dina  and
      Ananiadou, Sophia  and
      Roberts, Kirk  and
      Tsujii, Junichi",
    booktitle = "{B}io{NLP} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.bionlp-1.21/",
    pages = "250--267",
    ISBN = "979-8-89176-434-7",
    abstract = "This paper introduces LEA-Dialog, a multi-turn diagnostic dialogue dataset for lower-extremity arteriovenous diseases, together with a carefully developed diagnostic handbook and a process-aligned agentic framework for structured outpatient diagnosis. The dataset provides stage annotations for each turn and guideline-grounded probability trends, enabling evaluation beyond final diagnostic accuracy. Experiments show that the framework improves reasoning stability and reduces drift across both online and offline LLMs, with particularly large gains for smaller offline models."
}