人工智能在中医临床疗效评价中的应用现状及未来发展对策
Application status and future development countermeasures of artificial intelligence in the evaluation of clinical efficacy of traditional Chinese medicine
展志宏 1戴国华 2张丛惠 2任丽丽 1管慧 2高武霖2
作者信息
- 1. 山东中医药大学第一临床医学院,济南 250014
- 2. 山东中医药大学附属医院,济南 250014
- 折叠
摘要
中医临床疗效评价是中医药现代化研究的重要内容,传统的疗效评价处理方法与技术已经无法满足中医药诊疗的快速发展需求.在以人工智能为代表的数据驱动大环境下,将信息科学技术与中医药优势相融合,采用科学的方法构建中医临床疗效评价体系,已成为当前中医临床疗效研究的关键方向.文章通过论述人工智能在中医临床疗效评价中的应用现状及存在的问题,提出构建临床信息采集平台及评价指标数据库的发展对策.通过选取的人工智能技术加深数据处理,优化层次结构,完善体系内容,以期为中医临床疗效评价的创新发展提供新的解决思路.
Abstract
Clinical efficacy evaluation of traditional Chinese medicine is an important part of the modernization research of traditional Chinese medicine.The traditional treatment methods and techniques of efficacy evaluation have been unable to meet the rapid development needs of diagnosis and treatment of traditional Chinese medicine.In the data-driven environment represented by artificial intelligence,to integrate information science technology with the advantages of traditional Chinese medicine,and use scientific methods to build a clinical efficacy evaluation system of traditional Chinese medicine has become the key direction of current research on clinical efficacy of traditional Chinese medicine.This paper discusses the application status and existing problems of artificial intelligence in the evaluation of clinical efficacy of traditional Chinese medicine,and proposed development strategies for building a clinical information collection platform and evaluation index database.Through the selected artificial intelligence technology,the data processing is deepened,the hierarchical structure is optimized,and the content of the system is improved,in order to provide new solutions for the innovative development of traditional Chinese medicine clinical efficacy evaluation.
关键词
人工智能/疗效评价/评价指标/四诊信息/数据库Key words
Artificial intelligence/Curative effect evaluation/Evaluation index/Four diagnosis information/Database引用本文复制引用
基金项目
国家科技部国家重点研发计划中医药现代化研究重点专项(2019YFC1710401)
国家自然科学基金面上项目(82174172)
国家自然科学基金青年科学基金(82204942)
山东省自然科学基金青年基金(ZR2022QH123)
中国博士后科学基金面上项目(2022M721998)
出版年
2024
NETL
NSTL
万方数据