基于知识增强的医学语言模型:现状、技术与应用 |
修订日期:2023-09-19 点此下载全文 |
引用本文:康砚澜,郭倩宇,张文强,等.基于知识增强的医学语言模型:现状、技术与应用[J].医学信息学杂志,2023,44(9):12-22 |
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基金项目:国家自然科学基金项目(项目编号:62176185)。 |
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中文摘要:目的/意义 介绍生成式语言模型在医学领域的应用现状和挑战,并提出一种基于知识增强的医学语言模型,以提高模型专业性、准确性和可信性,为医学、语言模型及知识图谱领域相关研究人员提供参考。方法/过程 回顾大语言模型的发展、现状及主要技术,分析其在数据安全、专业性、伦理规范和模型可解释性等方面面临的挑战。介绍医学生成式语言模型常见应用场景和技术要点,重点阐述基于知识图谱和多模态数据融合知识增强的医学语言模型,包括其优势、技术原理和具体案例。结果/结论 知识增强的医学语言模型可提高语言模型对专业医学知识的理解、认知和应用能力,增强对自然语言的生成能力,拓展对多模态数据的处理能力,在医疗问答、智能辅助诊断、个性化医疗决策等方面具有广泛应用前景。 |
中文关键词:生成式语言模型 医学问答 知识图谱 人工智能 医疗 |
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Knowledge-enhanced Medical Language Models:Current Status, Techniques, and Applications |
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Abstract:Purpose/Significance The paper introduces the application status and challenges of generative language model in the medical field, and proposes a knowledge-enhanced medical language model to improve the specialization, accuracy and credibility of the model, and provides references for researchers in the fields of medicine, language model and knowledge graph. Method/Process It reviews the development, current status, and major technologies of large language models, and analyzes the challenges in data security, professionalism, ethics, and model interpretability. It introduces the common application scenarios and technical points of medical generative language model, and focuses on the medical language model based on knowledge graph and multi-modal data fusion knowledge enhancement, including the advantages, technical principles and specific cases. Result/Conclusion The knowledge-enhanced medical language model can improve the understanding, cognition and application capability of language model to professional medical knowledge, enhance the generative capability of natural language, and expand the processing capability of multi-modal data, which has a wide application prospect in medical question answering, intelligent assisted diagnosis, personalized medical decision making and so on. |
keywords:generative language model medical question answering knowledge graph artificial intelligence(AI) medical treatment |
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