Analysis of the Research Status and Hot Spot of Intelligent Four-Diagnosis in TCM

LI Hong-yan; LI Can; LANG Xu-feng; YANG Tao; ZHOU Zuo-jian; ZHAN Li-bin

doi:10.14148/j.issn.1672-0482.2022.0180

Volume 38 Issue 2

Feb. 2022

Turn off MathJax

Article Contents

Article Navigation > Journal of Nanjing University of traditional Chinese Medicine > 2022 > 38(2): 180-186

LI Hong-yan, LI Can, LANG Xu-feng, YANG Tao, ZHOU Zuo-jian, ZHAN Li-bin. Analysis of the Research Status and Hot Spot of Intelligent Four-Diagnosis in TCM[J]. Journal of Nanjing University of traditional Chinese Medicine, 2022, 38(2): 180-186. doi: 10.14148/j.issn.1672-0482.2022.0180

Citation:

LI Hong-yan, LI Can, LANG Xu-feng, YANG Tao, ZHOU Zuo-jian, ZHAN Li-bin. Analysis of the Research Status and Hot Spot of Intelligent Four-Diagnosis in TCM[J]. Journal of Nanjing University of traditional Chinese Medicine, 2022, 38(2): 180-186. doi: 10.14148/j.issn.1672-0482.2022.0180

Citation:

PDF( 7770 KB)

Analysis of the Research Status and Hot Spot of Intelligent Four-Diagnosis in TCM

doi: 10.14148/j.issn.1672-0482.2022.0180

1.
School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing 210023, China
2.
Centre for Innovative Engineering Technology in Traditional Chinese Medicine, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, China

Received Date: 2021-10-18
Available Online: 2022-03-01

Abstract

Abstract

As the basic means of traditional Chinese medicine (TCM) diagnosis and syndrome differentiation, the four-diagnosis of TCM has been further inherited and innovated under the empowerment of artificial intelligence in recent years. In this paper, we summarized the Chinese and English literature of the four-diagnosis intelligent research of TCM in the past ten years, analyzed its current research status, completed the visual analysis based on the knowledge graph, and further discussed the research hot-spots in this field. Finally, based on the existing research status, we proposed thinking and prospects for the next development of the intellectualization of the TCM four-diagnostics, in order to provide reference value and significance for the future research in this area.
- the four-diagnosis of TCM,
- intelligence,
- research status,
- research hot-spots,
- visualization

FullText(HTML)

References(45)

References

[1]	郭振球. 中医辨证学与人工智能[J]. 湖南中医学院学报, 1982, 2(1): 5-8. https://www.cnki.com.cn/Article/CJFDTOTAL-HNZX198201001.htm GUO ZQ. TCM syndrome differentiation and artificial intelligence[J]. J Tradit Chin Med Univ Hunan, 1982, 2(1): 5-8. https://www.cnki.com.cn/Article/CJFDTOTAL-HNZX198201001.htm
[2]	迪盼祺, 夏春明, 王忆勤, 等. 基于协同过滤算法的中医智能问诊系统研究[J]. 世界科学技术-中医药现代化, 2021, 23(1): 247-255. https://www.cnki.com.cn/Article/CJFDTOTAL-SJKX202101041.htm DI PQ, XIA CM, WANG YQ, et al. Research on intelligent Chinese medical consultation system based on collaborative filtering algorithm[J]. Mod Tradit Chin Med Mater Med World Sci Technol, 2021, 23(1): 247-255. https://www.cnki.com.cn/Article/CJFDTOTAL-SJKX202101041.htm
[3]	颜建军, 孙钰晨, 燕海霞, 等. 基于血压标定的中医脉图信号分析识别研究[J]. 辽宁中医杂志, 2020, 47(8): 13-17. https://www.cnki.com.cn/Article/CJFDTOTAL-LNZY202008005.htm YAN JJ, SUN YC, YAN HX, et al. Analysis and recognition of TCM pulse signals based on blood pressure calibration[J]. Liaoning J Tradit Chin Med, 2020, 47(8): 13-17. https://www.cnki.com.cn/Article/CJFDTOTAL-LNZY202008005.htm
[4]	陈瑞, 刘璐, 王忆勤, 等. 人工神经网络在中医舌面诊中的研究进展[J]. 中华中医药杂志, 2020, 35(4): 1924-1926. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY202004083.htm CHEN R, LIU L, WANG YQ, et al. Research progress of artificial neural network in the tongue-face diagnosis of traditional Chinese medicine[J]. China J Tradit Chin Med Pharm, 2020, 35(4): 1924-1926. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY202004083.htm
[5]	王忆勤. 中医诊断技术发展及四诊信息融合研究[J]. 上海中医药大学学报, 2019, 33(1): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-SHZD201901001.htm WANG YQ. Development of TCM diagnostic technology and fusion research for four-diagnosis information[J]. Acad J Shanghai Univ Tradit Chin Med, 2019, 33(1): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-SHZD201901001.htm
[6]	颜建军, 李东旭, 郭睿, 等. 基于深度学习和随机森林的齿痕舌分类研究[J/OL]. 中华中医药学刊, 2021: 1-12. https://kns.cnki.net/kcms/detail/21.1546.R.20210813.1632.016.html. YAN JJ, LI DX, GUO R, et al. Research on the classification of dentate tongue based on deep learning and random forest[J/OL]. Chin Arch Tradit Chin Med, 2021: 1-12. https://kns.cnki.net/kcms/detail/21.1546.R.20210813.1632.016.html.
[7]	颜建军, 刘章鹏, 刘国萍, 等. 基于深度森林算法的慢性胃炎中医证候分类[J]. 华东理工大学学报(自然科学版), 2019, 45(4): 593-599. https://www.cnki.com.cn/Article/CJFDTOTAL-HLDX201904011.htm YAN JJ, LIU ZP, LIU GP, et al. Syndrome classification of chronic gastritis based on multi-grained cascade forest[J]. J East China Univ (Sci Technol), 2019, 45(4): 593-599. https://www.cnki.com.cn/Article/CJFDTOTAL-HLDX201904011.htm
[8]	WANG YQ, YAN HX, GUO R, et al. Study on intelligent syndrome differentiation in traditional Chinese medicine based on multiple information fusion methods[J]. Int J Data Min Bioinform, 2011, 5(4): 369-382. doi: 10.1504/IJDMB.2011.041554
[9]	林怡, 王斌, 许家佗, 等. 基于面部图像特征融合的中医望诊面色分类研究[J]. 实用临床医药杂志, 2020, 24(14): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-XYZL202014001.htm LIN Y, WANG B, XU JT, et al. Facial color classification of traditional Chinese medicine inspection based on fusion of facial image features[J]. J Clin Med Pract, 2020, 24(14): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-XYZL202014001.htm
[10]	石玉琳, 胡晓娟, 许家佗. 中医病证智能化诊断与分类研究进展[J]. 中国中西医结合杂志, 2019, 39(6): 763-768. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZXJ201906033.htm SHI YL, HU XJ, XU JT. Intelligent diagnosis and classification research development of Chinese medical syndrome typing[J]. Chin J Integr Tradit West Med, 2019, 39(6): 763-768. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZXJ201906033.htm
[11]	陈梦竹, 岑翼刚, 许家佗, 等. 基于图像处理的望诊面色自动识别研究[J]. 中国中医药信息杂志, 2018, 25(12): 97-101. doi: 10.3969/j.issn.1005-5304.2018.12.023 CHEN MZ, CEN YG, XU JT, et al. Study on observation diagnosis automatic complexion recognition based on image processing[J]. Chin J Inf Tradit Chin Med, 2018, 25(12): 97-101. doi: 10.3969/j.issn.1005-5304.2018.12.023
[12]	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. https://www.cnki.com.cn/Article/CJFDTOTAL-DEJD201808010.htm CUI J, XU JT. Diagnosis and treatment technologies of traditional Chinese medicine: Application and prospect in context of artificial intelligence[J]. Acad J Second Mil Med Univ, 2018, 39(8): 846-851. https://www.cnki.com.cn/Article/CJFDTOTAL-DEJD201808010.htm
[13]	徐熊, 宋海贝, 温川飙, 等. 基于智能信息处理的舌诊客观化研究[J]. 电脑知识与技术, 2020, 16(22): 182-184, 197. https://www.cnki.com.cn/Article/CJFDTOTAL-DNZS202022073.htm XU X, SONG HB, WEN CB, et al. Progress in objectification of tongue diagnosis based on intelligent information processing[J]. Comput Knowl Technol, 2020, 16(22): 182-184, 197. https://www.cnki.com.cn/Article/CJFDTOTAL-DNZS202022073.htm
[14]	宋海贝, 温川飙, 程小恩. 基于AI的中医舌象面象辅助诊疗系统构建[J]. 时珍国医国药, 2020, 31(2): 502-505. https://www.cnki.com.cn/Article/CJFDTOTAL-SZGY202002083.htm SONG HB, WEN CB, CHENG XE. Construction of an aI-based TCM tongue and facial aided diagnosis and treatment system[J]. Lishizhen Med Mater Med Res, 2020, 31(2): 502-505. https://www.cnki.com.cn/Article/CJFDTOTAL-SZGY202002083.htm
[15]	何黎, 曹悦, 胡远樟, 等. 基于中医"治未病"理论的中医四诊在中医体检中的应用及意义[J]. 科学技术创新, 2020(3): 4-6. https://www.cnki.com.cn/Article/CJFDTOTAL-HLKX202003003.htm HE L, CAO Y, HU YZ, et al. Application and significance of four diagnoses in TCM physical examination based on the theory of TCM "preventing diseases"[J]. Sci Technol Innov, 2020(3): 4-6. https://www.cnki.com.cn/Article/CJFDTOTAL-HLKX202003003.htm
[16]	谢天宇, 曹继忠, 温川飙. 名老中医传承四诊信息"后结构化"的关键技术探讨[J]. 世界最新医学信息文摘, 2018, 18(62): 211-212. https://www.cnki.com.cn/Article/CJFDTOTAL-WMIA201862112.htm XIE TY, CAO JZ, WEN CB. Discussion on the key technology of four diagnostic information "post-structured" of inheritance of old Chinese medicine[J]. World Latest Med Inf, 2018, 18(62): 211-212. https://www.cnki.com.cn/Article/CJFDTOTAL-WMIA201862112.htm
[17]	王东军, 杨欢, 田之魁, 等. 中医舌象特征客观化研究领域科学知识图谱与可视化分析[J]. 世界科学技术-中医药现代化, 2021, 23(9): 3032-3040. WANG DJ, YANG H, TIAN ZK, et al. Scientific knowledge map and visualization analysis in the field of research on the objectification of tongue features in Chinese medicine[J]. Mod Tradit Chin Med Mater Med World Sci Technol, 2021, 23(9): 3032-3040.
[18]	王东军, 孙璇, 田之魁, 等. 肺癌的舌象研究现状[J]. 时珍国医国药, 2021, 32(7): 1718-1719. doi: 10.3969/j.issn.1008-0805.2021.07.52 WANG DJ, SUN X, TIAN ZK, et al. Tongue image research status of lung cancer[J]. Lishizhen Med Mater Med Res, 2021, 32(7): 1718-1719. doi: 10.3969/j.issn.1008-0805.2021.07.52
[19]	WEN GH, WANG KW, LI HH, et al. Recommending prescription via tongue image to assist clinician[J]. Multimed Tools Appl, 2021, 80(9): 14283-14304. doi: 10.1007/s11042-020-10441-3
[20]	FAN BC, LI YH, WEN GH, et al. Personalized body constitution inquiry based on machine learning[J]. J Healthc Eng, 2020, 2020: 8834465. http://ieeexplore.ieee.org/document/9057416
[21]	WEN GH, MA JJ, HU Y, et al. Grouping attributes zero-shot learning for tongue constitution recognition[J]. Artif Intell Med, 2020, 109: 101951. doi: 10.1016/j.artmed.2020.101951
[22]	LIAO HQ, WEN GH, HU Y, et al. Convolutional herbal prescription building method from multi-scale facial features[J]. Multimed Tools Appl, 2019, 78(24): 35665-35688. doi: 10.1007/s11042-019-08118-7
[23]	MA JJ, WEN GH, WANG CJ, et al. Complexity perception classification method for tongue constitution recognition[J]. Artif Intell Med, 2019, 96: 123-133. doi: 10.1016/j.artmed.2019.03.008
[24]	LI HH, WEN GH, ZENG HB. Natural tongue physique identification using hybrid deep learning methods[J]. Multimed Tools Appl, 2019, 78(6): 6847-6868. doi: 10.1007/s11042-018-6279-8
[25]	SHI YL, LIU JY, HU XJ, et al. A new method for syndrome classification of non-small-cell lung cancer based on data of tongue and pulse with machine learning[J]. Biomed Res Int, 2021, 2021: 1337558. http://www.ncbi.nlm.nih.gov/pubmed/34423031
[26]	JIANG T, HU XJ, YAO XH, et al. Tongue image quality assessment based on a deep convolutional neural network[J]. BMC Med Inform Decis Mak, 2021, 21(1): 147. doi: 10.1186/s12911-021-01508-8
[27]	LI J, CHEN QG, HU XJ, et al. Establishment of noninvasive diabetes risk prediction model based on tongue features and machine learning techniques[J]. Int J Med Inform, 2021, 149: 104429. doi: 10.1016/j.ijmedinf.2021.104429
[28]	LI J, YUAN P, HU XJ, et al. A tongue features fusion approach to predicting prediabetes and diabetes with machine learning[J]. J Biomed Inform, 2021, 115: 103693. doi: 10.1016/j.jbi.2021.103693
[29]	LUO ZY, CUI J, HU XJ, et al. A study of machine-learning classifiers for hypertension based on radial pulse wave[J]. Biomed Res Int, 2018, 2018: 2964816. http://www.researchgate.net/publication/328883630_A_Study_of_Machine-Learning_Classifiers_for_Hypertension_Based_on_Radial_Pulse_Wave/fulltext/5be9874f4585150b2bb12dcb/328883630_A_Study_of_Machine-Learning_Classifiers_for_Hypertension_Based_on_Radial_Pulse_Wave.pdf?origin=publication_detail
[30]	MENG D, CAO GT, DUAN Y, et al. Tongue images classification based on constrained high dispersal network[J]. Evid Based Complement Alternat Med, 2017, 2017: 7452427. http://europepmc.org/articles/pmc5390589?pdf=render
[31]	QI Z, TU LP, CHEN JB, et al. The classification of tongue colors with standardized acquisition and ICC profile correction in traditional Chinese medicine[J]. Biomed Res Int, 2016, 2016: 3510807. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5168476/pdf/BMRI2016-3510807.pdf
[32]	FAN SY, CHEN B, ZHANG XR, et al. Machine learning algorithms in classifying TCM tongue features in diabetes mellitus and symptoms of gastric disease[J]. Eur J Integr Med, 2021, 43: 101288. http://www.sciencedirect.com/science/article/pii/S1876382021000068
[33]	周常恩, 赵文, 许鸿本, 等. 以状态为核心的中医健康状态辨识系统构建研究[J]. 中华中医药杂志, 2021, 36(8): 4849-4852. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY202108110.htm ZHOU CE, ZHAO W, XU HB, et al. Research on establishment of status-centered traditional Chinese medicine health status identification system[J]. China J Tradit Chin Med Pharm, 2021, 36(8): 4849-4852. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY202108110.htm
[34]	徐佳君, 雷黄伟, 高新皓, 等. 人工智能与中医诊断技术[J]. 天津中医药, 2021, 38(5): 560-564. https://www.cnki.com.cn/Article/CJFDTOTAL-TJZY202105005.htm XU JJ, LEI HW, GAO XH, et al. Artificial intelligence and traditional Chinese medicine diagnostic technology[J]. Tianjin J Tradit Chin Med, 2021, 38(5): 560-564. https://www.cnki.com.cn/Article/CJFDTOTAL-TJZY202105005.htm
[35]	李灿东, 辛基梁, 雷黄伟, 等. 中医健康管理与人工智能[J]. 中华中医药杂志, 2019, 34(8): 3586-3588. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY201908067.htm LI CD, XIN JL, LEI HW, et al. Health management of traditional Chinese medicine and artificial intelligence[J]. China J Tradit Chin Med Pharm, 2019, 34(8): 3586-3588. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY201908067.htm
[36]	梁文娜, 林雪娟, 俞洁, 等. 真实世界的大数据助推中医健康管理进入人工智能时代[J]. 中华中医药杂志, 2018, 33(4): 1213-1215. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY201804001.htm LIANG WN, LIN XJ, YU J, et al. Big database of real world promotes health management of traditional Chinese medicine into artificial intelligence era[J]. China J Tradit Chin Med Pharm, 2018, 33(4): 1213-1215. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY201804001.htm
[37]	XIA SJ, GAO BZ, WANG SH, et al. Modeling of diagnosis for metabolic syndrome by integrating symptoms into physiochemical indexes[J]. Biomed Pharmacother, 2021, 137: 111367. http://www.sciencedirect.com/science/article/pii/S0753332221001529
[38]	WENG H, LI L, LEI HW, et al. A weakly supervised tooth-mark and crack detection method in tongue image[J]. Concurr Comput Pract Exp, 2021, 33(16): e6262.
[39]	XIA SJ, ZHANG J, DU GD, et al. A microcosmic syndrome differentiation model for metabolic syndrome with multilabel learning[J]. Evid Based Complement Alternat Med, 2020, 2020: 9081641.
[40]	LI L, LUO ZM, ZHANG MT, et al. An iterative transfer learning framework for cross-domain tongue segmentation[J]. Concurr Comput Pract Exp, 2020, 32(14): e5714. doi: 10.1002/cpe.5714/full
[41]	李渊彤, 罗裕升, 朱珍民. 基于深度学习的舌象特征分析[J]. 计算机科学, 2020, 47(11): 148-158. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJA202011022.htm LI YT, LUO YS, ZHU ZM. Tongue image analysis in traditional Chinese medicine based on deep learning[J]. Comput Sci, 2020, 47(11): 148-158. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJA202011022.htm
[42]	刘佳丽, 孙自强. 基于Double-D算法的舌像检测[J]. 计算机工程与设计, 2020, 41(7): 2025-2030. https://www.cnki.com.cn/Article/CJFDTOTAL-SJSJ202007035.htm LIU JL, SUN ZQ. Tongue image detection based on Double-D algorithm[J]. Comput Eng Des, 2020, 41(7): 2025-2030. https://www.cnki.com.cn/Article/CJFDTOTAL-SJSJ202007035.htm
[43]	孙康宁, 孙琦, 李新霞, 等. 基于卷积神经网络的中医面色提取识别研究[J]. 中华中医药杂志, 2021, 36(7): 4286-4290. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY202107125.htm SUN KN, SUN Q, LI XX, et al. Research on TCM color extraction and recognition based on the convolutional neural network[J]. China J Tradit Chin Med Pharm, 2021, 36(7): 4286-4290. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYY202107125.htm
[44]	张嘉琪, 张月琴, 陈健. 优化强化学习路径特征分类的脉象识别法[J]. 计算机应用, 2021, 41(11): 3402-3408. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY202111044.htm ZHANG JQ, ZHANG YQ, CHEN J. Pulse condition recognition method based on optimized reinforcement learning path feature classification[J]. J Comput Appl, 2021, 41(11): 3402-3408. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY202111044.htm
[45]	李勐, 湛月, 袁柳, 等. 三点位同步测量中医脉诊机器人系统设计实现[J]. 科学技术与工程, 2021, 21(26): 11220-11225. https://www.cnki.com.cn/Article/CJFDTOTAL-KXJS202126028.htm LI M, ZHAN Y, YUAN L, et al. Design and implementation of a three-point simultaneous pulse examination robotic system[J]. Sci Technol Eng, 2021, 21(26): 11220-11225. https://www.cnki.com.cn/Article/CJFDTOTAL-KXJS202126028.htm

Relative Articles

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(2) / Tables(1)

Get Citation

PDF

XML

Article Metrics

Article views (519) PDF downloads(144)

Analysis of the Research Status and Hot Spot of Intelligent Four-Diagnosis in TCM

doi: 10.14148/j.issn.1672-0482.2022.0180

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Analysis of the Research Status and Hot Spot of Intelligent Four-Diagnosis in TCM

doi: 10.14148/j.issn.1672-0482.2022.0180

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Export File

Citation

Format

Content