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Study on Screening of Main Acupoints and Pattern-Specific Acupoint Combination Rules for Acupuncture in Autism Spectrum Disorder Complicated with Sleep Disorder Based on Data Mining
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作者 Wei Du Hujie Song 《Journal of Clinical and Nursing Research》 2025年第8期241-249,共9页
Objective:To explore the core acupuncture acupoints and pattern-adapted acupoint combination rules for autism spectrum disorder(ASD)complicated with sleep disorder using clinical data mining technology.Methods:A retro... Objective:To explore the core acupuncture acupoints and pattern-adapted acupoint combination rules for autism spectrum disorder(ASD)complicated with sleep disorder using clinical data mining technology.Methods:A retrospective analysis was conducted on the diagnosis and treatment data of 104 children with ASD complicated with sleep disorder admitted to Xi’an Traditional Chinese Medicine(TCM)Encephalopathy Hospital from January 2022 to December 2024.Cross-pattern main acupoints were screened via frequency statistics,chi-square test,and factor analysis;pattern-specific auxiliary acupoints were extracted by combining multiple correspondence analysis,cluster analysis,and association rule mining.Results:Ten cross-pattern main acupoints(Baihui,Sishenzhen,Language Area 1,Language Area 2,Neiguan,Shenmen,Yongquan,Xuanzhong)were identified,and acupoint combination schemes for four major TCM patterns(Hyperactivity of Liver and Heart Fire,Deficiency of Kidney Essence,Deficiency of Both Heart and Spleen,Hyperactivity of Liver with Spleen Deficiency)were established.Conclusion:Acupuncture treatment should follow the principle of“regulating spirit and calming the brain as the root,and dredging collaterals based on pattern differentiation as the branch”.The synergy between main and auxiliary acupoints can accurately regulate the disease,providing a basis for precise clinical treatment. 展开更多
关键词 Autism Spectrum Disorder(ASD) Sleep disorder Acupoint selection rule data mining
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Spatial Multidimensional Association Rules Mining in Forest Fire Data
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作者 Imas Sukaesih Sitanggang 《Journal of Data Analysis and Information Processing》 2013年第4期90-96,共7页
Hotspots (active fires) indicate spatial distribution of fires. A study on determining influence factors for hotspot occurrence is essential so that fire events can be predicted based on characteristics of a certain a... Hotspots (active fires) indicate spatial distribution of fires. A study on determining influence factors for hotspot occurrence is essential so that fire events can be predicted based on characteristics of a certain area. This study discovers the possible influence factors on the occurrence of fire events using the association rule algorithm namely Apriori in the study area of Rokan Hilir Riau Province Indonesia. The Apriori algorithm was applied on a forest fire dataset which containeddata on physical environment (land cover, river, road and city center), socio-economic (income source, population, and number of school), weather (precipitation, wind speed, and screen temperature), and peatlands. The experiment results revealed 324 multidimensional association rules indicating relationships between hotspots occurrence and other factors.The association among hotspots occurrence with other geographical objects was discovered for the minimum support of 10% and the minimum confidence of 80%. The results show that strong relations between hotspots occurrence and influence factors are found for the support about 12.42%, the confidence of 1, and the lift of 2.26. These factors are precipitation greater than or equal to 3 mm/day, wind speed in [1m/s, 2m/s), non peatland area, screen temperature in [297K, 298K), the number of school in 1 km2 less than or equal to 0.1, and the distance of each hotspot to the nearest road less than or equal to 2.5 km. 展开更多
关键词 data mining spatial association rule HOTSPOT OCCURRENCE APRIORI Algorithm
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Mining multilevel spatial association rules with cloud models 被引量:2
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作者 杨斌 朱仲英 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2005年第3期314-318,共5页
The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates ... The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules. Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible. 展开更多
关键词 cloud model spatial association rules virtual cloud spatial data mining
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A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge 被引量:6
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作者 LIU Yaolin XIE Peng +3 位作者 HE Qingsong ZHAO Xiang WEI Xiaojian TAN Ronghui 《Chinese Geographical Science》 SCIE CSCD 2017年第3期389-401,共13页
Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results conta... Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors. 展开更多
关键词 data mining association rules rules spatial visualization driving factors analysis land use change
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Mining association rule efficiently based on data warehouse 被引量:3
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作者 陈晓红 赖邦传 罗铤 《Journal of Central South University of Technology》 2003年第4期375-380,共6页
The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) i... The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the minimal and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed. By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm. 展开更多
关键词 data mining association rule mining COMPLETE association rule SET least association rule SET
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CARM:Context Based Association Rule Mining for Conventional Data 被引量:1
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作者 Muhammad Shaheen Umair Abdullah 《Computers, Materials & Continua》 SCIE EI 2021年第9期3305-3322,共18页
This paper is aimed to develop an algorithm for extracting association rules,called Context-Based Association Rule Mining algorithm(CARM),which can be regarded as an extension of the Context-Based Positive and Negativ... This paper is aimed to develop an algorithm for extracting association rules,called Context-Based Association Rule Mining algorithm(CARM),which can be regarded as an extension of the Context-Based Positive and Negative Association Rule Mining algorithm(CBPNARM).CBPNARM was developed to extract positive and negative association rules from Spatiotemporal(space-time)data only,while the proposed algorithm can be applied to both spatial and non-spatial data.The proposed algorithm is applied to the energy dataset to classify a country’s energy development by uncovering the enthralling interdependencies between the set of variables to get positive and negative associations.Many association rules related to sustainable energy development are extracted by the proposed algorithm that needs to be pruned by some pruning technique.The context,in this paper serves as a pruning measure to extract pertinent association rules from non-spatial data.Conditional Probability Increment Ratio(CPIR)is also added in the proposed algorithm that was not used in CBPNARM.The inclusion of the context variable and CPIR resulted in fewer rules and improved robustness and ease of use.Also,the extraction of a common negative frequent itemset in CARM is different from that of CBPNARM.The rules created by the proposed algorithm are more meaningful,significant,relevant and insightful.The accuracy of the proposed algorithm is compared with the Apriori,PNARM and CBPNARM algorithms.The results demonstrated enhanced accuracy,relevance and timeliness. 展开更多
关键词 association rules CONTEXT CBPNARM non-spatial data CPIR SUPPORT CONFIDENCE INTERESTINGNESS
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Improvement of Mining Fuzzy Multiple-Level Association Rules from Quantitative Data 被引量:1
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作者 Alireza Mirzaei Nejad Kousari Seyed Javad Mirabedini Ehsan Ghasemkhani 《Journal of Software Engineering and Applications》 2012年第3期190-199,共10页
Data-mining techniques have been developed to turn data into useful task-oriented knowledge. Most algorithms for mining association rules identify relationships among transactions using binary values and find rules at... Data-mining techniques have been developed to turn data into useful task-oriented knowledge. Most algorithms for mining association rules identify relationships among transactions using binary values and find rules at a single-concept level. Extracting multilevel association rules in transaction databases is most commonly used in data mining. This paper proposes a multilevel fuzzy association rule mining model for extraction of implicit knowledge which stored as quantitative values in transactions. For this reason it uses different support value at each level as well as different membership function for each item. By integrating fuzzy-set concepts, data-mining technologies and multiple-level taxonomy, our method finds fuzzy association rules from transaction data sets. This approach adopts a top-down progressively deepening approach to derive large itemsets and also incorporates fuzzy boundaries instead of sharp boundary intervals. Comparing our method with previous ones in simulation shows that the proposed method maintains higher precision, the mined rules are closer to reality, and it gives ability to mine association rules at different levels based on the user’s tendency as well. 展开更多
关键词 association rule data mining FUZZY Set Quantitative Value TAXONOMY
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Spatial Data Mining to Support Environmental Management and Decision Making--A Case Study in Brazil
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作者 Carlos Roberto Valencio Fernando Tochio Ichiba Guilherme Priollli Daniel Rogeria Cristiane Gratao de Souza Leandro Alves Neves Angelo Cesar Colombini 《Computer Technology and Application》 2014年第1期25-32,共8页
The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transf... The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transform raw data into useful previously unknown information. However, due to the high complexity of spatial data mining, the need for spatial relationship comprehension and its characteristics, efforts have been directed towards improving algorithms in order to provide an increase of performance and quality of results. Likewise, several issues have been addressed to spatial data mining, including environmental management, which is the focus of this paper. The main original contribution of this work is the demonstration of spatial data mining using a novel algorithm with a multi-relational approach that was applied to a database related to water resource from a certain region of S^o Paulo State, Brazil, and the discussion about obtained results. Some characteristics involving the location of water resources and the profile of who is administering the water exploration were discovered and discussed. 展开更多
关键词 Water resource management spatial data mining multi-relational spatial data mining spatial clustering environmentalmanagement.
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Unveiling the prescription patterns and mechanisms of Chinese herbal compound patents in the management of acute appendicitis:A data mining investigation
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作者 Yuewen Li Qinsheng Zhang Suqin Hu 《Journal of Chinese Pharmaceutical Sciences》 2025年第6期566-580,共15页
In the present study,data mining and network pharmacology were utilized to explore the principles and mechanisms of traditional Chinese medicine(TCM)in treating acute appendicitis.The goal was to provide a scientific ... In the present study,data mining and network pharmacology were utilized to explore the principles and mechanisms of traditional Chinese medicine(TCM)in treating acute appendicitis.The goal was to provide a scientific basis for clinical treatment and further research on this disease.First,we searched the National Patent Database for Chinese herbal compound prescriptions used to treat acute appendicitis.We then applied frequency analysis,character and taste meridian analysis,association rule analysis,and hierarchical cluster analysis to identify the patterns of TCM treatment for acute appendicitis,selecting key combinations of Chinese medicines.Next,we screened the main active components of these key TCM based on quality markers.Using databases such as SwissTargetPrediction,SymMap,ETCM,and STRING,we analyzed the pharmacological mechanisms of these key TCM in treating acute appendicitis.Key active components and targets were further verified through molecular docking.We identified a total of 129 patents involving 316 Chinese medicines,with 24 being frequently used.The results indicated that most Chinese herbs used for acute appendicitis were heat-clearing drugs,blood-activating and stasis-removing drugs,and purging drugs.The primary active ingredients of the Rhubarb-cortex moutan-flos lonicerae combination for treating acute appendicitis included Emodin,Paeonol,Physcion,Chlorogenic acid,Chrysophanol,Rhein acid,and Aloe-emodin.These ingredients targeted key proteins such as ALB,TP53,BCL2,STAT3,IL-6,and TNF,and were involved in cellular responses to lipopolysaccharides,cell composition,and various cytokine-mediated biological processes.They also interacted with signaling pathways like AGE-RAGE,TNF,IL-17,and FoxO.Based on patent data,this study analyzed medication patterns in the treatment of acute appendicitis,discussed the possible mechanisms of key TCM combinations,and provided a scientific basis and new perspectives for the diagnosis and treatment of the disease. 展开更多
关键词 Acute appendicitis data mining rule of composition Hierarchical clustering Molecular docking
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Unveiling core acupoints in acupuncture treatment for primary depressive disorder:integrating data mining and network acupuncture-based analysis
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作者 Siyu LIU Xinnan LUOa Jiayun XIE +2 位作者 Miqun ZHOU Xiaona HU Shuang SONG 《Digital Chinese Medicine》 2025年第4期504-516,共13页
Objective To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder(PDD)through data mining and network analysis.Methods A comprehensive literature search... Objective To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder(PDD)through data mining and network analysis.Methods A comprehensive literature search was conducted across PubMed,Embase,Ovid Technologies(OVID),Web of Science,Cochrane Library,China National Knowledge Infrastructure(CNKI),China National Knowledge Infrastructure Database(VIP),Wanfang Data,and SinoMed Database from database foundation to January 31,2025,for clinical studies on acupuncture treatment of PDD.Descriptive statistics,high-frequency acupoint analysis,degree and betweenness centrality evaluation,and core acupoint prescription mining identified predominant therapeutic combinations for PDD.Network acupuncture was used to predict therapeutic target for the core acupoint prescription.Subsequent protein-protein interaction(PPI)network and molecular complex detection(MCODE)analyses were conducted to identify the key targets and functional modules.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses explored the underlying biological mechanisms of the core acupoint prescription in treating PDD.Results A total of 57 acupoint prescriptions underwent systematic analysis.The core therapeutic combinations comprised Baihui(GV20),Yintang(GV29),Neiguan(PC6),Hegu(LI4),and Shenmen(HT7).Network acupuncture analysis identified 88 potential therapeutic targets(79 overlapping with PDD),while PPI network analysis revealed central regulatory nodes,including interleukin(IL)-6,IL-1β,tumor necrosis factor(TNF)-α,toll-like receptor 4(TLR4),IL-10,brain-derived neurotrophic factor(BDNF),transforming growth factor(TGF)-β1,C-XC motif chemokine ligand 10(CXCL10),mitogen-activated protein kinase 3(MAPK3),and nitric oxide synthase 1(NOS1).MCODE-based modular analysis further elucidated three functionally coherent clusters:inflammation-homeostasis(score=6.571),plasticity-neurotransmission(score=3.143),and oxidative stress(score=3.000).GO and KEGG analyses demonstrated significant enrichment of the MAPK,phosphoinositide 3-kinase/protein kinase B(PI3K/Akt),and hypoxia-inducible factor(HIF)-1 signaling pathways.These mechanistic insights suggested that the antidepressant effects mediated through mechanisms of neuroinflammatory regulation,neuroplasticity restoration,and immune-oxidative stress homeostasis.Conclusion This study reveals that acupuncture alleviates depression through a multi-level mechanism,primarily involving the neuroinflammation suppression,neuroplasticity enhancement,and oxidative stress regulation.These findings systematically clarify the underlying mechanisms of acupuncture’s antidepressant effects and identify novel therapeutic targets for further mechanistic research. 展开更多
关键词 ACUPUNCTURE Primary depressive disorder(PDD) data mining Network acupuncture association analysis
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Optimization and principles of acupoint selection and coordination in the treatment of adult abdominal obesity using acupuncture and moxibustion over the past decade:A data mining
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作者 Jia-xin SHEN Tian-yun HUANG +4 位作者 Zhou HAO Guang-bin PENG Yue-ying MA Huan-gan WU Chun-hui BAO 《World Journal of Acupuncture-Moxibustion》 2025年第3期223-231,共9页
Objective To explore the optimization and principles of acupoint selection and coordination in the treatment of adult abdominal obesity using acupuncture and moxibustion over the past decade using data mining.Methods ... Objective To explore the optimization and principles of acupoint selection and coordination in the treatment of adult abdominal obesity using acupuncture and moxibustion over the past decade using data mining.Methods Clinical studies of abdominal obesity treated with acupuncture and moxibustion,collected in the past 10 years,were searched from China Biology Medicine disc(CBMdisc),China National knowledge infrastructure(CNKI),Wanfang,China Science and Technology Journal Database(VIP),Pubmed,Embase,Google Scholar,Web of Science,(The Cumulative Index to Nursing and Allied Health Literature)CINAHL,Psyclnfo and Scopus,dated from March 1,2013 to March 31,2023.Using IBM SPSS Modeler 18.0 and other software,the frequency analysis,association-rules analysis and cluster analysis were conducted on interventions,traditional Chinese medicine(TCM)patterns,use frequency of acupoint,meridian attribution of acupoint,acupoint location,etc.Results A total of 55 articles were included,with 102 prescriptions and 71 acupoints involved.The top 3 interventions were acupoint embedding method,simple electroacupuncture and simple filiform needling.Seventeen patterns/syndromes of TCM differentiation were collected,dominated by spleen deficiency and damp blockage,spleen and kidney yang deficiency and heat accumulation in stomach and intestines.The acupoints in clinical practice were mostly at the foot-yangming stomach meridian,the conception vessel and the foot-taiyin spleen meridian,and located at the abdominal region.The top 5 acupoints of high frequency were Tianshu(ST25),Zhongwan(CV12),Daheng(SP15),Zusanli(ST36),Huaroumen(ST24)and Daimai(GB26).The specific points of the high frequency were the crossing points and front-mu points,of which,ST25 and CV12 were the most prominent.After association-rules analysis on the high-frequency acupoints,20 groups of associated acupoints were obtained,in which,the core acupoints included ST25,CV12,SP15 and ST36.Conclusion In recent 10 years,abdominal obesity is treated by the acupoints of foot-yangming stomach meridian,the conception vessel and the foot-taiyin spleen meridian.Compared with the regimen for simple obesity,the acupoints at the abdominal region are specially selected in treatment of abdominal obesity,such as ST25,CV12,SP15 and ST36.Supplementary acupoints are selected based on syndrome differentiation to simultaneously address both the disease manifestations and root causes. 展开更多
关键词 Abdominal obesity Acupuncture and moxibustion data mining rules of acupoint selection
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Mining Time Pattern Association Rules in Temporal Database
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作者 Nguyen Dinh Thuan 《通讯和计算机(中英文版)》 2010年第3期50-56,共7页
关键词 挖掘关联规则 时间模式 时态数据库 大型数据库 时间间隔 优化技术 验算法
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Acupoint selection rules in acupuncture therapy for postoperative urinary retention after hemorrhoidectomy based on data mining technology 被引量:3
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作者 Qi-jie LI Meng-di ZHOU +5 位作者 Zheng-ting DUAN Tai-wei HUANG Xin DENG Lu CAI Shi-ru LIU Hong-yan LI 《World Journal of Acupuncture-Moxibustion》 CSCD 2022年第1期70-77,共8页
Objective:To explore the core acupoints and combination rules of acupuncture therapy for postoperative urinary retention after hemorrhoidectomy,and,further to analyze the characteristics of the prescription of acupunc... Objective:To explore the core acupoints and combination rules of acupuncture therapy for postoperative urinary retention after hemorrhoidectomy,and,further to analyze the characteristics of the prescription of acupuncture therapy for postoperative urinary retention after hemorrhoidectomy.Methods:Relevant clinical studies in seven databases were searched systematically from database inception to 1 st October 2020.Based on data mining techniques,the core acupoints,characteristics and combination rules of acupuncture therapy for postoperative urinary retention after hemorrhoidectomy were analyzed comprehensively.Statistics collected and analysis of acupoint selection included the frequency of usage of acupoints,the meridian of acupoints,the location of acupoints and the combination of acupoints.Cluster and association analysis were performed utilizing Excel 13.0 and SPSS 26.0.Results:In the 36 studies included,the most frequently adopted acupoint was Sānyīnjiāo(三阴交 SP6);the most frequently adopted meridian was the foot-taiyin spleen meridian;the most frequently involved location was the lower limbs;and the most frequently adopted combination of acupoints was SP6 and Zhōngjí(中极CV 3).Cluster analysis showed that the acupoints could be divided into three categories:the first group comprised SP6 alone;the second group included CV3,Guānyuán(关元CV4),Yīnlíngquán(阴陵泉SP9) and Zúsānlǐ(足三里ST36);and the third group included Pángguāngshū(膀胱俞BL28),Chéngshān(承山BL57),Tàichōng(太冲LR3),Zhìbiān(秩边 BL54),Tàixī(太溪KI6),Hégǔ(合谷 LI4),Xuèhǎi(血海SP10),Qìhǎi(气海CV6) and Shǔidào(水道ST28).Conclusion:It was found that acupuncture therapy for postoperative urinary retention after hemorrhoidectomy mainly follows the four characteristic rules:the selection of acupoints following the meridian,selection of acupoints at local points,selection of acupoints at distal points and selection of acupoints according to special symptoms. 展开更多
关键词 ACUPUNCTURE Acupoint selection rules data mining Postoperative urinary retention HEMORRHOIDS
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Medication Rules of Hub Herb Pairs for Insomnia and Mechanism of Action:Results of Data Mining,Network Pharmacology,and Molecular Docking 被引量:1
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作者 Wen-Long Guo Hui-Juan Jiang +2 位作者 Yan-Rong Li Jin-Long Yang Yu-Chan Chen 《Chinese Medical Sciences Journal》 CAS CSCD 2024年第4期249-260,共12页
Objective To explore the medication rules of traditional Chinese medicine(TCM)and mechanism of action of hub herb pairs for treating insomnia.Methods Totally 104 prescriptions were statistically analyzed.The associati... Objective To explore the medication rules of traditional Chinese medicine(TCM)and mechanism of action of hub herb pairs for treating insomnia.Methods Totally 104 prescriptions were statistically analyzed.The association rule algorithm was applied to mine the hub herb pairs.Network pharmacology was utilized to analyze the mechanism of the hub herb pairs,while molecular docking was applied to simulate the interaction between receptors and herb molecules,thereby predicting their binding affinities.Results The most frequently used herbs in TCM prescriptions for treating insomnia included Semen Ziziphi Spinosae,Radix Glycyrrhizae,Radix et Rhizoma Ginseng,and Poria cum Radix Pini.Among them,the most commonly used were the supplementing herbs,followed by heat-clearing,mind-calming,and exterior-releasing ones,with their properties of warm and cold,flavors of sweet,Pungent,and bitter,and meridian tropisms of liver,lungs,spleen,kidneys,heart,and stomach.The hub herb pairs based on the association rules included Radix Astragali-Radix et Rhizoma Ginseng,Rhizoma Chuanxiong-Radix Glycyrrhizae,Seman Platycladi-Semen Ziziphi Spinosae,Pericarpium Citri Reticulatae-Radix Glycyrrhizae,Radix Polygalae-Semen Ziziphi Spinosae,and Radix Astragali-Semen Ziziphi Spinosae.Network pharmacology revealed that the cAMP signaling pathway might play a key role in treating insomnia synergistically with HIF-1 signaling pathway,prolactin signaling pathway,chemical carcinogenesis receptor activation,and PI3K-Akt signaling pathway.Molecular docking indicated that there was good binding between the active ingredients of the hub herb pairs and the hub targets.Conclusions This study identified six hub herb pairs for treating insomnia in TCM.These hub herb pairs may synergistically treat insomnia with HIF-1 signaling pathway,prolactin signaling pathway,chemical carcinogenesis receptor activation,and PI3K-Akt signaling pathway through the cAMP signaling pathway. 展开更多
关键词 medication rules mechanism INSOMNIA data mining herb pairs network pharmacology molecular docking
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A study on the rule of Chinese medicine use against influenza virus based on data mining 被引量:1
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作者 Yu-Qiang Lu Lin FU +4 位作者 Yu-Qi Hao Hui Ding Zhao-Lin Shi Ru-Ying Li Guo-Cheng Zhang 《Medical Data Mining》 2021年第1期28-37,共10页
Background:To summarize the rules of the use of traditional Chinese medicine against influenza virus in the high-quality literatures of core journals,and to provide guidance for the prevention and treatment of influen... Background:To summarize the rules of the use of traditional Chinese medicine against influenza virus in the high-quality literatures of core journals,and to provide guidance for the prevention and treatment of influenza.Methods:Excel 2010 and ancient and modern medical case cloud platform(2.5V)were used to summarize the categories,nature,flavour and channel tropism of drugs.The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and the association rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 18.0.Results:One thousand one hundred and thirty-one articles from core journals were retrieved and 135 articles were screened out,including 109 prescriptions and 170 drugs,with a total frequency of 1,655 times.The 3 most frequently appeared herbs were Gancao(Glycyrrhizae radix et rhizoma),Jinyinhua(Lonicerae japonicae flos)and Lianqiao(Forsythiae fructus).The top 3 efficacy were“Heat-Clearing(remove heat from the body surface and inside)”drugs,drugs for“Relieving Exterior Disorder(treat fever,chills and headaches caused by pathogenic substances in the air)”,and“Phlegm Relieving Cough Antiasthmatic Medicine(relieves respiratory cough and sputum symptoms)”drugs.The top 3 nature of drugs were cold,warm and flat.The top 3 flavour of drugs were bitter,spicy and sweet.The top 5 channel tropism of drugs were“Lung”,“Stomach”,“Heart”,“Spleen”,“Liver”.Association rule yields 20 drug pairs,Jingjie(Schizonepetae herba),Forsythiae fructus,Lonicerae japonicae flos,Niubangzi(Arctii fructus),Mahuang(Ephedrae herba)and Glycyrrhizae radix et rhizoma were commonly used concerted application;four new methods were obtained by cluster analysis.Conclusion:The use of traditional Chinese medicine against influenza virus has a certain regularity,which provides an important reference value for the prevention and treatment of influenza. 展开更多
关键词 Traditional Chinese medicine The flu Medication rule data mining
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Spatial data mining system for ore-forming prediction 被引量:1
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作者 Man WANG Linfu XUE Yingwei WANG 《Global Geology》 2007年第1期100-104,共5页
The authors designed the spatial data mining system for ore-forming prediction based on the theory and methods of data mining as well as the technique of spatial database,in combination with the characteristics of geo... The authors designed the spatial data mining system for ore-forming prediction based on the theory and methods of data mining as well as the technique of spatial database,in combination with the characteristics of geological information data.The system consists of data management,data mining and knowledge discovery,knowledge representation.It can syncretize multi-source geosciences data effectively,such as geology,geochemistry,geophysics,RS.The system digitized geological information data as data layer files which consist of the two numerical values,to store these files in the system database.According to the combination of the characters of geological information,metallogenic prognosis was realized,as an example from some area in Heilongjiang Province.The prospect area of hydrothermal copper deposit was determined. 展开更多
关键词 ore-forming prediction spatial data mining multi-source geoscience data
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Database Encoding and A New Algorithm for Association Rules Mining
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作者 Tong Wang Pilian He 《通讯和计算机(中英文版)》 2006年第3期77-81,共5页
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Study on the medication rules of traditional Chinese medicine in the treatment of sleep disorder after stroke based on data mining
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作者 Xian Liu Jia-Xin Jin +4 位作者 Li-Li He Peng-Zhen Ma Su-Su Ma Yu-Xuan Du Ying-Zhen Xie 《Journal of Hainan Medical University》 2022年第10期50-58,共9页
Objective:To explore the medication rule of Traditional Chinese Medicine(TCM)in the treatment of sleep disorder after stroke by using data mining technology.Methods:A computer search was used to search the electronic ... Objective:To explore the medication rule of Traditional Chinese Medicine(TCM)in the treatment of sleep disorder after stroke by using data mining technology.Methods:A computer search was used to search the electronic database of clinical literature on the treatment of sleep disorders after stroke by TCM from January 2000 to January 2021.Excel was used to establish the database,and the prescription information was described and analyzed statistically.Using IBM SPSS Modeler 18.0 software,Apriori algorithm was used for TCM association analysis,and IBM SPSS 22.0 software was used for systematic cluster analysis of high-frequency TCM.Results:A total of 67 literatures were included,covering 131 traditional Chinese medicines.The medecines with a higher frequency of sodium use include Ziziphi Spinosae Semen(Suanzaoren),Angelicae Sinensis Radix(Danggui),Ligusticum(Chuanxiong),liquorice(Gancao),Poria cocos(Fuling),and so on.From the effect point of view,deficiency-tonifying medicine,sedative medicine and blood-activating and stasis-removing medicine are commonly used.The medicinal properties are mainly cold,mild and warm.The main medicine flavor are sweet and bitter.The medicines mostly belong to the liver,heart and spleen Meridian.Thirty-three association rules were obtained for medicine pairs and medicine groups from the correlation analysis,and the core combinations were"Ziziphi Spinosae Semen(Suanzaoren)-Tuber fleeceflower stem(Yejiaoteng)","Ziziphi Spinosae Semen(Suanzaoren)-Polygala(Yuanzhi)","Ziziphi Spinosae Semen(Suanzaoren)-Cortex albiziae(Hehuanpi)"and"Angelicae Sinensis Radix(Danggui)-Radix bupleuri(Chaihu)-Radix Paeoniae Alba(Baishao)"and so on.Seven medicine aggregation groups were obtained by medicine cluster analysis.Conclusion:In the treatment of sleep disorder after stroke by TCM,the main method is to calm the heart and mind.Meanwhile,according to different syndrome types,the treatment methods of tonifying the heart and spleen,nourishing the liver and kidney,soothing the liver and softening the liver,clearing heat and resolving phlegm,nourishing the blood and promoting blood circulation are selected,which provide certain reference for clinical treatment. 展开更多
关键词 data mining Sleep disorder after stroke Medication rule association analysis Clustering analysis
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Study on prescription and medication rules of Hua Baojin for treatment of colorectal cancer based on data mining
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作者 Meng-Qi Cheng Yu-Wei Zhao +2 位作者 Ju-Ling Jiang Hong-Gang Zheng Bao-Jin Hua 《Journal of Hainan Medical University》 2022年第4期53-59,共7页
Objective:To study the prescription and medication rule of Professor Hua Baojin in the treatment of colorectal cancer through data mining,so as to provide reference for clinical treatment of colorectal cancer. Methods... Objective:To study the prescription and medication rule of Professor Hua Baojin in the treatment of colorectal cancer through data mining,so as to provide reference for clinical treatment of colorectal cancer. Methods:The outpatient medical records of Professor Hua Baojin from June 2015 to October 2020 in Guang’anmen Hospital,China Academy of Chinese Medical Sciences were collected. TCM Inheritance Support Platform(V2.5)was used to analyze high-frequency drugs,drug properties,flavors,channel tropism,common drug combinations,core combinations and new prescriptions. Results:A total of 500 prescriptions were included,involving 222 traditional Chinese medicines and 38 high-frequency(≥100)medicines,including Atractylodes,Poria cocos,ginger,etc. The most common medicinal properties of drugs were warm,cold and mild,and flavors were sweet,bitter and pungent,channel tropism included spleen,stomach,liver and lung meridians. 36 groups of common drug combinations and 20 association rules were obtained by data mining,and 18 core combinations and 9 new prescriptions were evolved.Conclusion:Professor Hua Baojin takes recuperating spleen and stomach as the core in the treatment of colorectal cancer,attaching importance to regulating the rise and fall of qi,adding and subtracting on the basis of Xiangsha Liujunzi Decoction,flexibly selecting the drugs of dispelling blood stasis,resolving phlegm,detoxification and loose knots,and using both cold and warm in the prescription,tonifying and reducing at the same time. 展开更多
关键词 Hua Baojin Colorectal cancer data mining Medication rule
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Study on the rules of TCM syndromes and Chinese herbal medicines about IgAN based on data mining
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作者 Hong-Tong Chen Cai-Di Gong +3 位作者 Chong Xiong Jian Zhong Zi-Xia Wang Ping Chen 《Journal of Hainan Medical University》 2021年第12期38-42,共5页
Objective:To analyze the clinical research literatures of TCM syndromes and treatment of Immunoglobulin A Nephropathy(IgAN)on data-mining technology,and explore the rules of TCM syndromes and Chinese medication.Method... Objective:To analyze the clinical research literatures of TCM syndromes and treatment of Immunoglobulin A Nephropathy(IgAN)on data-mining technology,and explore the rules of TCM syndromes and Chinese medication.Methods:By searching the clinical literatures about TCM syndromes and treatment of IgAN had published in China Biomedical Literature Database,CNKI Database,Wanfang Database,and Chongqing Weipu Database from January 2000 to September 2019.Strictly according to the inclusion and exclusion criteria,included documents and established the databases.Applicated of statistical software for frequency analysis of TCM syndromes,Chinese herbal medicines,and analyzed the commonly used Chinese herbal medicines by factor analysis and cluster analysis.Results:292 literatures were finally included,involving 28 syndromes.A total of 479 prescriptions and 254 Chinese herbs were used.The rules of syndromes in IgA nephropathy are as follows:the syndromes are mainly composed of Qi and Yin deficiency syndrome,followed by the Spleen and kidney qi deficiency syndrome,Liver and Kidney Yin Deficiency Syndrome,Spleen and kidney yang deficiency syndrome.The blood-stasis syndrome,damp-heat syndrome and wind-heat disturbance syndrome are accompanied by other syndrome.The characteristics of traditional Chinese medicines for IgA nephropathy is mainly composed of tonic deficiency medicines,supplemented by blood-activating and stasis-eliminating medicines,heat-clearing medicines,inducing diuresis and excreting dampness medicines and astringent medicines to combine with formulas.Conclusion:Through Data-mining method systematically summarized the rules of TCM syndromes and Chinese medication in treating IgAN and provided scientific theoretical guidance for the treatment of IgAN. 展开更多
关键词 Immunoglobulin A nephropathy Traditional Chinese Medicine SYNDROMES rules of medication data mining
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