| 引用本文: |
文志华,肖莉,刘青萍,苏祥飞,陈佑邦,晏峻峰,彭清华.中医症状规范化、标准化研究进程及问题探讨[J].湖南中医药大学学报,2023,43(12):2294-2299[点击复制] |
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| 中医症状规范化、标准化研究进程及问题探讨 |
| 文志华,肖莉,刘青萍,苏祥飞,陈佑邦,晏峻峰,彭清华 |
| (湖南中医药大学信息科学与工程学院, 湖南 长沙 410208;湖南工业大学计算机学院, 湖南 株洲 412000;湖南中医药大学中医诊断研究所, 湖南 长沙 410208;中华中医药学会, 北京 100029;湖南中医药大学信息科学与工程学院, 湖南 长沙 410208;湖南中医药大学中医诊断研究所, 湖南 长沙 410208) |
| 摘要: |
| 症状是中医辨证论治的重要依据。症状规范化、标准化有助于中医诊断学规范化研究，进一步推动中医数字化、智能化研究进程。中医的现代化、数字化、智能化以及中医药国际化传播、中医诊断学内涵发展对中医症状规范、标准研究产生了积极影响。通过对文献梳理总结了已有症状规范化、标准化研究的方法与成果，对症状规范化、标准化过程中的标准症状命名、症状客观性表达、症状粒度选择以及症状量化等问题进行分析与探讨，总结了症状规范化标准化过程中常用的机器学习、深度学习等技术，并从信息化视角提出标准症状词库五步构建方法，为中医诊断研究以及中医辨证诊断数字化、智能化研究提供症状规范基础。 |
| 关键词: 症状 症状术语 症状规范化 症状标准化 中医信息化 |
| DOI：10.3969/j.issn.1674-070X.2023.12.022 |
| 投稿时间：2023-08-29 |
| 基金项目:国家自然科学基金面上项目（82274588）；湖南省教育厅科学研究重点项目（21A0250）；湖南中医药大学中医学一流学科开放基金重点项目（2022ZYX08）。 |
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| Research progress and discussion of the TCM symptoms normalization and standardization |
| WEN Zhihua,XIAO Li,LIU Qingping,SU Xiangfei,CHEN Youbang,YAN Junfeng,PENG Qinghua |
| (School of Informatics, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;School of Computer Science, Hunan University of Technology, Zhuzhou, Hunan 412000, China;TCM Diagnostic Institute, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;China Association of Chinese Medicine, Beijing 100029, China;School of Informatics, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;TCM Diagnostic Institute, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China) |
| Abstract: |
| Symptom is an important element for TCM pattern differentiation and treatment. The normalization and standardization of symptoms can contribute to the further in-depth study of TCM diagnostics, and can also accelerate the digital and intelligent research process of TCM.Vice versa, the modernization, digitization, intellectualization, the international dissemination of TCM, and the development of TCM diagnostics pose a positive impact on the research of the normalization and standardization of TCM symptoms. By reviewing the literature, we summarized the methods and results of the existing normalized and standardized research on symptoms, furtherly, analyzed and discussed some important issues such as the naming of standard symptoms, the objective expression, the granularity selection, and the quantization. To sum up, we have summarized the common techniques of machine learning and deep learning in symptom standardization and normalization, and proposed a five-step construction method of standard symptom lexicon from the perspective of information technology. It has provided the symptom standard basis for TCM diagnosis research and the digital intelligent research of TCM pattern differentiation diagnosis. |
| Key words: symptom symptom terminology symptom normalization symptom standardization TCM informatization |
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