摘要
针灸学的发展源于古代医家们不断的探索和临床实践,在大量经验的积累总结上形成了独特的诊疗模式。文章在剖析传统针灸临床诊疗技术发展瓶颈的基础上,提出采用人工智能等现代科学技术以构建面向临床症状的智能选穴模式。鉴于针灸文献数据的复杂性以及临床模式的多样性,采用具有效力和可信度的评价方法与挖掘算法,输出带效力和可信度标注的频繁选穴模式以及按等级推荐选穴方案的算法,以确保其有效性(效力性研究)与科学性(可信度评价)。该选穴模式为针灸临床诊疗模式的客观量化研究提供了新的突破口,初步构建了传统针灸理论及其现代临床运用的智能化研究范式。
Acupuncture is derived from ancient clinical practice. Long-term clinical practice has accumulated a special diagnosis and therapy system. This paper discusses the bottlenecks for the development of clinical diagnosis and treatment techniques in acupuncture. Then, we propose a clinical symptom-oriented intelligent acupoint selection model using artificial intelligence(AI) technology. In view of complexity of acupuncture literatures and variety of the clinical patterns, an evaluation methodology and data mining method based on potency and credibility was used. In order to ensure the validity and scientificalness, the frequent pattern for acupoint selection outputs is noted with potency and credibility, and the algorithm for that outputs are noted with grades of recommendation. This acupoint selection pattern provide a breakthrough for model of acupuncture clinical diagnosis and treatment, and an intelligent research paradigm was initially constructed, which connects traditional acupuncture theories and its modern clinical application.
作者
齐诗仪
倪友聪
章思佳
杜欣
林丽莉
林栋
QI Shi-yi;NI You-cong;ZHANG Sijia;DU Xin;LIN Li-li;LIN Dong(Fujian University of Traditional Chinese Medicine,Fuzhou 350122,China;Fujian Normal University,Fuzhou 350117,China)
出处
《中华中医药杂志》
CAS
CSCD
北大核心
2022年第12期7220-7223,共4页
China Journal of Traditional Chinese Medicine and Pharmacy
基金
国家自然科学基金面上项目(No.82074521)。
关键词
针灸
人工智能
数据挖掘
算法
穴位
诊疗模式
Acupuncture
Artificial intelligence(AI)
Data mining
Algorithm
Acupoint
Diagnosis and treatment pattern
