本研究对大语言模型(large language model,LLM)、数据查询机器人(data query robot,DQR)的发展历程和研究现状进行了介绍,同时通过实证分析,探讨了在数字医学领域中,基于LLM的DQR的实际应用效果及其在处理医疗数据查询和分析的复杂任务中的作用,证实了基于LLM的DQR能为非技术人员提供一个直观且便捷的工具,显著提升医疗数据的查询效率和分析能力.此外,本文还探讨了 LLM和DQR技术在当前应用中的局限性及未来发展潜力,为进一步的研究和应用提供参考.
Abstract
This study introduced the development history and current research status of large language model(LLM),data query robot(DQR).Meanwhile,through empirical analyses,the practical application effect of LLM-based DQR and its role in dealing with the complex tasks of medical data querying and analysis in the field of digital medicine was explored,and it was confirmed that LLM-based DQR could provide non-technical people with an intuitive and convenient tool to significantly improve the querying efficiency and analysis capability of medical data.In addition,this paper discusses the limitations and potential of future development of LLM and DQR techniques in current applications,providing reference for further research and applications.
关键词
大语言模型/数据查询机器人/数字医学/自然语言处理/深度学习
Key words
Large language model/Data query robot/Digital medicine/Natural language processing/Deep learning
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