| 引用本文: |
高远,张仕娜,盛博洋,董云春,庞瑞涵,晏峻峰,彭清华.由ChatGPT引发中医智能诊断研究中数据问题的思考[J].湖南中医药大学学报,2023,43(7):1320-1324[点击复制] |
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| 由ChatGPT引发中医智能诊断研究中数据问题的思考 |
| 高远,张仕娜,盛博洋,董云春,庞瑞涵,晏峻峰,彭清华 |
| (湖南中医药大学, 湖南 长沙 410208;湖南中医药大学中医诊断研究所, 湖南 长沙 410208;湖南中医药大学, 湖南 长沙 410208;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, 湖南 长沙 410208;湖南中医药大学中医诊断研究所, 湖南 长沙 410208;湖南中医药大学信息科学与工程学院, 湖南 长沙 410208) |
| 摘要: |
| ChatGPT作为现象级产品受到广泛关注，本文从数据的数量、质量、驱动和保护4个方面，通过阐述ChatGPT的数据特点，引发中医智能诊断研究中数据问题的思考。中医智能诊断研究需要建立数据共享模式和中医诊断的数据元标准，以解决中医智能诊断研究中数据的数量和质量问题。多学科团队需要基于中医诊断知识进行推理，并且需要大数据对中医诊断知识推理规则调整参数、优化算法，共同构建融合知识与数据驱动方法，实现认知智能的中医智能诊断系统，以增强计算机推理结果的逻辑性和可解释性。中医学者在数据共享的同时，也要保护中医诊断数据的版权与安全。这些数据关系人民与国家的数据安全，关系我国全民健康情况和我国卫生事业的发展趋势。 |
| 关键词: ChatGPT 中医 人工智能 辨证 数据 版权 安全 |
| DOI：10.3969/j.issn.1674-070X.2023.07.027 |
| 投稿时间：2023-03-15 |
| 基金项目:湖南省研究生科研创新项目（QL20220183，QL20220184，CX20210716）；湖南省教育厅重点项目（21A0250）；湖南中医药大学中医学一流学科开放基金项目（2022ZYX08，2021ZYX31）；湖南中医药大学研究生创新课题（2022CX02，2022CX118）。 |
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| Thoughts on data issues in intelligent diagnosis research of TCM prompted by ChatGPT |
| GAO Yuan,ZHANG Shina,SHENG Boyang,DONG Yunchun,PANG Ruihan,YAN Junfeng,PENG Qinghua |
| (Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;Institute of TCM Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;School of Informatics, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;Institute of TCM Diagnostics, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;School of Informatics, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China) |
| Abstract: |
| As a phenomenal product, ChatGPT has received widespread attention. This paper expounds the data features of ChatGPT from aspects of data quantity, quality, driving, and protection, prompting thoughts on data issues in intelligent diagnosis research of TCM. In order to solve the problems related with data quantity and quality in intelligent diagnosis research of TCM, it is necessary to establish data sharing model and data element standard for it. Furthermore, knowledge reasoning need to be conducted based on TCM diagnostic knowledge by multidisciplinary teams; big data is needed to adjust parameters and optimize algorithms for TCM diagnostic knowledge reasoning rules; TCM intelligent diagnostic systems should be jointly built to integrate knowledge and data-driven methods. The above measures help achieve cognitive intelligence and enhance the logic and interpretability of computer reasoning results. In addition, TCM academics should protect the copyright and security of TCM diagnostic data while sharing. These data determine the data security, and concern the health situation of Chinese people and the development of health service. |
| Key words: ChatGPT TCM artificial intelligence pattern differentiation data copyright security |
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