REN Jin-yu,BAI Lin*,ZHONG Hua.Design and Implementation of TCM Auxiliary Diagnosis and Treatment Recommendation System[J].Chinese Journal of Library and Information Science for Traditional Chinese Medicine,2021,45(3):1-5.[doi:10.3969/j.issn.2095-5707.2021.03.001]
中医辅助诊疗推荐系统设计与实现
- Title:
- Design and Implementation of TCM Auxiliary Diagnosis and Treatment Recommendation System
- 文章编号:
- 2095-5707(2021)03-0001-05
- 分类号:
- TP311.5;R241
- 文献标志码:
- A
- 摘要:
- 目的 研究和开发辅助中医医生诊疗的中医辅助诊疗推荐系统。方法 以中医历史病案数据为基础,利用数据挖掘技术和度量学习技术挖掘、整理中医诊疗经验知识,建立病案相似度计算方法,设计中医辅助诊疗推荐系统功能框架并开发应用系统。结果 设计并构建了中医辅助诊疗推荐系统,在四诊识别阶段为医生推荐候选症状,在辨证论治阶段为医生推荐诊疗方案,从而辅助经验不足的医生诊疗。结论 该系统可以在临床实践中辅助医生诊疗,从而降低中医传承难度、改善中医传承模式,更好地发展和利用中医药。
- Abstract:
- Objective To research and develop a TCM auxiliary diagnosis and treatment recommendation system. Methods Based on TCM historical medical record data, this article established a method for calculating the similarity of medical records, designed the functional framework of TCM auxiliary diagnosis and treatment recommendation system, and developed the application system by using data mining technology and metric learning technology to mine and sort out the experience and knowledge of TCM diagnosis and treatment. Results A TCM auxiliary diagnosis and treatment recommendation system was built, which could recommend symptoms for doctors in the process of TCM four diagnostic methods, and recommend diagnosis and treatment plans for doctors in the stage of syndrome differentiation and treatment, so as to assist inexperienced doctors in diagnosis and treatment. Conclusion The system can assist TCM diagnosis and treatment in clinical practice, so as to reduce the difficulty of TCM inheritance, improve TCM inheritance model, and better develop and use TCM.
参考文献/References:
[1] 崔骥,许家佗.人工智能背景下中医诊疗技术的应用与展望[J].第二军医大学学报,2018,39(8):846-851.
[2] 陈辛畋,阮春阳,于观贞,等.融“古”贯“今”,构建智慧中医新体系[J].第二军医大学学报,2018,39(8):826-829.
[3] 刘伟,丁长松,梁杨.中药种质资源信息系统的设计与实现[J].中国中医药信息杂志,2017,24(5):5-7.
[4] 刘健,蒋卫民,沈宫建.面向大数据的高血压中医专家诊疗系统构建及应用[J].中国中医药图书情报杂志,2019,43(5):5-9.
[5] 王倩,石艳敏,史春晖,等.基于云平台Hadoop的中医数据挖掘系统设计与实现[J].计算机应用与软件,2018,35(10):45-48,79.
[6] 卢朋,李健,唐仕欢,等.中医传承辅助系统软件开发与应用[J].中国实验方剂学杂志,2012,18(9):1-4.
[7] 范元赫,杨永菊,关雪峰.基于中医传承辅助系统分析骨质疏松组方用药规律[J].辽宁中医药大学学报,2020,22(9):201-205.
[8] 李鹤,谢亚娟,厉启芳,等.基于中医传承辅助系统分析中医药治疗肝脾不调证溃疡性结肠炎的用药规律[J].中国医药,2020,15(10):1580-1584.
[9] 黄盛,祁烁,李会龙,等.基于中医传承辅助系统治疗甲状腺结节用药规律分析[J].世界中医药,2020,15(7):1025-1029.
[10] 宋洋,杨仁义,周德生,等.基于GEO数据与中医传承辅助系统分析气虚血瘀型脑梗死的中医药防治策略[J/OL].世界中医药[2021-01-23].http://kns.cnki.net/kcms/detail/11.5529.R.20201102.1145.010.html">http://kns.cnki.net/kcms/detail/11.5529.R.20201102.1145.010.html.
[11] 封继宏,张鹏宇.数据挖掘在现代中医药研究中的应用进展[J].中国医药导报,2020,17(13):54-57.
[12] 雷蕾,骆言,任静,等.基于数据挖掘对中医治疗慢性肾衰竭组方规律的分析[J].中成药,2019,41(12):3079-3082.
[13] 张玉娇,章新友,谈荣珍,等.基于循证的中药药性判别数据挖掘方法评价[J].中华中医药杂志,2019,34(3):1223-1226.
[14] 彭琳.基于数据挖掘的中医药治疗效果与用药规律关联性分析[J].科技通报,2019,35(1):77-81.
[15] YE Y, XE B, MA L, et al. Research on treatment and medication rule of insomnia treated by TCM based on data mining[C]// 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). San Diego, 2019:2503-2508.
[16] 王妮,黄艳群,刘红蕾,等.基于半监督学习的患者相似性度量研究[J].北京生物医学工程,2020,39(2):152-157.
[17] NI J Z, LIU J, ZHANG C X, et al. Fine-grained patient similarity measuring using deep metric learning[C]// Association for Computing Machinery. 2017 ACM on Conference on Information and Knowledge Management (CIKM). New York, 2017:1189-1198.
[18] ZHANG J, CHANG D. Semi-supervised patient similarity clustering algorithm based on electronic medical records[J]. IEEE Access, 2019(7):90705-90714.
[19] YAN X F, YU P, HAN J W. Graph indexing: a frequent structure-based approach[C]// Association for Computing Machinery. Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data (SIGMOD’04). New York, 2004:335-346.
备注/Memo
收稿日期:2021-03-05
更新日期/Last Update:
2021-05-25