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RareAgents: Advancing Rare Disease Care through LLM-Empowered Multi-disciplinary Team ...

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  • معلومة اضافية
    • بيانات النشر:
      arXiv
    • الموضوع:
      2024
    • Collection:
      DataCite Metadata Store (German National Library of Science and Technology)
    • نبذة مختصرة :
      Rare diseases, despite their low individual incidence, collectively impact around 300 million people worldwide due to the vast number of diseases. The involvement of multiple organs and systems, and the shortage of specialized doctors with relevant experience make diagnosing and treating rare diseases more challenging than common diseases. Recently, agents powered by large language models (LLMs) have demonstrated notable applications across various domains. In the medical field, some agent methods have outperformed direct prompts in question-answering tasks from medical examinations. However, current agent frameworks are not well-adapted to real-world clinical scenarios, especially those involving the complex demands of rare diseases. To bridge this gap, we introduce RareAgents, the first LLM-driven multi-disciplinary team framework designed specifically for the complex clinical context of rare diseases. RareAgents integrates advanced Multidisciplinary Team (MDT) coordination, memory mechanisms, and medical ...
    • الرقم المعرف:
      10.48550/arxiv.2412.12475
    • الدخول الالكتروني :
      https://dx.doi.org/10.48550/arxiv.2412.12475
      https://arxiv.org/abs/2412.12475
    • Rights:
      Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode ; cc-by-4.0
    • الرقم المعرف:
      edsbas.D5BDFED7