摘要
中医证候量表日益成为中医证候转化为临床疗效评价指标的载体,但其仍然面临着标准化程度不够高、临床应用推广不够充分、"辨证-诊断-治疗-评价"一体化程度不强等瓶颈问题,如何将中医证候量表有效服务于临床成为值得关注和解决的问题。人工智能对于大数据的深度学习和融合能力带来的启示,使笔者提出将已有成功研制的量表、研制量表的方法学成果与人工智能有机融合的设想,试图将中医证候量表作为中医人工智能获取深度学习资料的途径,将人工智能作为中医证候量表临床推广应用的载体,为智能化中医药临床决策与疗效评价模式的构建提供思路。
TCM pattern scale is turning TCM patterns into the clinical curative effect evaluation parameters,but it still faces a lot of bottlenecks such as poor standardization,inadequate clinical application,and lack of"pattern differentiation-diagnosis-treatment-evaluation"integration.How to effectively apply the scale in clinical settings has become a problem worthy of attention and in need of solution.Artificial intelligence’s ability of deep learning and integration of big data has inspired the present researchers to put forward the hypothesis that integrates the existing scales,methodology of scale development and artifical intelligence.TCM scales may be used as the way for TCM artificial intelligence to access deep learning materials,and artificial intelligence as the means of clinical application of TCM pattern scale.The research provides reference for the development of intelligent TCM clinical decision making and efficacy evaluation.
作者
陈智慧
张会永
裴宇鹏
杨关林
于莉
张哲
肖蕾
刘继东
Chen Zhihui;Zhang Huiyong;Pei Yupeng;Yang Guanlin;Yu Li;Zhang Zhe;Xiao Lei;Liu Jidong(Liaoning Academy of Chinese Medical Sciences,Liaoning University of Traditional Chinese Medicine,Liaoning 110847,China;Affiliated Hospital of Liaoning University of Traditional Chinese Medicine,Liaoning 110032,China;Key Laboratory of Ministry of Education for TCM Visceral Manifestation Theory and Application,Liaoning University of Traditional Chinese Medicine,Liaoning 110847,China;Organization Department of Liaoning University of Traditional Chinese Medicine,Liaoning 110847,China)
出处
《北京中医药大学学报》
CAS
CSCD
北大核心
2021年第3期221-225,共5页
Journal of Beijing University of Traditional Chinese Medicine
基金
国家自然科学基金项目(No.81603504,No.81603468)
国家重点基础发展研究计划(973计划)项目(No.2014CB531704)
辽宁省教育厅课题(No.L201943)。
关键词
中医证候量表
中医人工智能
疗效评价
临床决策
TCM pattern scale
TCM artificial intelligence
efficacy evaluation
clinical decision-making