Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs

Zicen Liao; Yunhao Sun; Matthew Purver

Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs

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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.

Anthology ID:: 2026.bionlp-1.21
Volume:: BioNLP 2026
Month:: July
Year:: 2026
Address:: San Diego, California
Editors:: Dina Demner-Fushman, Sophia Ananiadou, Kirk Roberts, Junichi Tsujii
Venues:: BioNLP | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 250–267
Language:
URL:: https://aclanthology.org/2026.bionlp-1.21/
DOI:
Bibkey:
Cite (ACL):: Zicen Liao, Yunhao Sun, and Matthew Purver. 2026. Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs. In BioNLP 2026, pages 250–267, San Diego, California. Association for Computational Linguistics.
Cite (Informal):: Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs (Liao et al., BioNLP 2026)
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PDF:: https://aclanthology.org/2026.bionlp-1.21.pdf

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@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://aclanthology.org/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."
}

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    <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.</abstract>
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%0 Conference Proceedings
%T Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs
%A Liao, Zicen
%A Sun, Yunhao
%A Purver, Matthew
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Roberts, Kirk
%Y Tsujii, Junichi
%S BioNLP 2026
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California
%@ 979-8-89176-434-7
%F liao-etal-2026-diagnosing
%X 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.
%U https://aclanthology.org/2026.bionlp-1.21/
%P 250-267

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Markdown (Informal)

[Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs](https://aclanthology.org/2026.bionlp-1.21/) (Liao et al., BioNLP 2026)

Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs (Liao et al., BioNLP 2026)

ACL

Zicen Liao, Yunhao Sun, and Matthew Purver. 2026. Diagnosing Lower Extremity Arteriovenous Diseases Using Agentic LLMs. In BioNLP 2026, pages 250–267, San Diego, California. Association for Computational Linguistics.