ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge.
ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge.
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DOI：
10.7759/cureus.40895
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发表时间：
2023-06
期刊：
影响因子：
--
通讯作者：
Zhang Y
中科院分区：
文献类型：
--
作者：
Li Y;Li Z;Zhang K;Dan R;Jiang S;Zhang Y
目的 本研究的主要目的是通过创建一种提高医疗建议准确性的专门语言模型，解决 ChatGPT 等流行的大型语言模型 (LLM) 的医学知识中观察到的局限性。方法我们通过使用来自广泛使用的在线医疗咨询平台的 100,000 条医患对话的大型数据集来调整和完善大型语言模型元人工智能 (LLaMA)，从而实现了这一目标。为了尊重隐私问题，这些对话都经过清理和匿名处理。除了模型细化之外，我们还采用了自我导向的信息检索机制，允许模型访问和利用来自维基百科等在线资源的实时信息以及来自精选离线医学数据库的数据。结果根据现实世界的医患互动对模型进行微调，显着提高了模型了解患者需求并提供明智建议的能力。通过为模型配备来自可靠的在线和离线来源的自主信息检索，我们观察到其响应的准确性有了显着提高。结论 我们提出的 ChatDoctor 代表了医学法学硕士的重大进步，展示了在理解患者询问和提供准确建议方面的显着进步。鉴于医疗领域的高风险和低容错性，这种提供准确可靠信息的增强不仅是有益的，而且是必要的。
Objective The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in medical advice. Methods We achieved this by adapting and refining the large language model meta-AI (LLaMA) using a large dataset of 100,000 patient-doctor dialogues sourced from a widely used online medical consultation platform. These conversations were cleaned and anonymized to respect privacy concerns. In addition to the model refinement, we incorporated a self-directed information retrieval mechanism, allowing the model to access and utilize real-time information from online sources like Wikipedia and data from curated offline medical databases. Results The fine-tuning of the model with real-world patient-doctor interactions significantly improved the model's ability to understand patient needs and provide informed advice. By equipping the model with self-directed information retrieval from reliable online and offline sources, we observed substantial improvements in the accuracy of its responses. Conclusion Our proposed ChatDoctor, represents a significant advancement in medical LLMs, demonstrating a significant improvement in understanding patient inquiries and providing accurate advice. Given the high stakes and low error tolerance in the medical field, such enhancements in providing accurate and reliable information are not only beneficial but essential.
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发表时间：
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