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中医药领域大语言模型的研究进展与应用前景

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采用人工智能技术研发的中医药领域大语言模型,推动了中医药的创新与发展,对中医药的传承和创新具有重要意义.基于大语言模型的研究背景,阐述了中医药领域大语言模型的研究现状和研究过程,包括收集中医药领域数据信息、输入指令数据微调模型及选择不同评估方法评测模型性能三个关键任务.总结了中医药大语言模型的前沿技术,如提示工程、检索增强生成、人类反馈强化学习等理论应用,有效提升了大语言模型在中医药领域各种应用场景中的适应能力.分析了中医药大语言模型仍面临的困难及挑战,在数据隐私、伦理偏见、模型解释、技术难题、评估标准等方面仍需进一步优化提升.展望了未来中医药大语言模型的应用前景,将其与深度学习等先进人工智能技术相结合,并融合中医四诊信息、中药图像数据等多模态信息,可为大语言模型在中医药领域的发展提供新的思路,从而更好地服务中医辨证诊断、中药处方推荐、中医药知识图谱构建、中医药教育等各种应用场景.
Research Progress and Application Prospect of Large Language Model in the Traditional Chinese Medicine
The development of large language models in the field of Traditional Chinese Medicine(TCM)using artificial intelli-gence has significantly contributed to both the innovation and preservation of TCM.This paper outlines the current research status and process of large language models in TCM,focusing on three key tasks:collecting TCM data,fine-tuning models with specific instruc-tions,and using different methods to evaluate model performance.It also highlights cutting-edge techniques,such as prompt engineer-ing,retrieval-augmented generation,and reinforcement learning from human feedback,which have enhanced the models'adaptability in various TCM applications.The challenges faced by TCM language models,such as data privacy,ethical biases,model interpret-ability,technical difficulties,and evaluation standards,are also analyzed,indicating areas for further improvement.Looking ahead,the combination of these models with advanced AI techniques like deep learning,and the integration of multimodal information such as TCM diagnostic data and herbal images,can open new possibilities for large language models in TCM.This will enhance their applica-tion in areas like syndrome differentiation diagnosis,prescription recommendations,TCM knowledge graph construction,and TCM edu-cation.

traditional Chinese medicineartificial intelligencelarge language modelnatural language processing

李欣桐、马素芬、张丰聪、周扬、李小童、生慧

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山东中医药大学智能与信息工程学院,山东 济南 250355

山东中医药大学教务处,山东 济南 250355

山东中医药大学中医文献与文化研究院,山东 济南 250355

山东中医药大学教育部中医药经典理论实验室,山东 济南 250355

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中医药 人工智能 大语言模型 自然语言处理

2024

南京中医药大学学报
南京中医药大学

南京中医药大学学报

CSTPCD北大核心
影响因子:1.658
ISSN:1672-0482
年,卷(期):2024.40(12)