Association Rule Analysis Research Articles

Generation of a medicine food homology formula and its likely mechanism in treatment of microvascular angina.

Microvascular angina (MVA) is the most common cause of cardiac ischemic chest pain in patients without obstructive coronary artery disease (CAD) and lacks of effective treatment means. Medicine food homology (MFH) involves substances with both nutritional and medicinal qualities that have the potential to improve MVA symptoms as medicines, dietary supplements. However, research on MFH formula (MFHF) for MVA is not available. The study aims to generate a core MFHF for MVA through data mining and offer scientific backing for the utilization of edible medications in the prevention and alleviation of MVA. 11 databases were utilized to construct a database of MFH drugs, and the MFHF was generated through frequency analysis, association rule analysis, and clustering analysis. The composition of the formula is Codonopsis Radix, Astragali Radix, Platycodonis Radix, Persicae Semen, Glycyrrhizae Radix Et Rhizoma, Angelicae Sinensis Radix, and Allii Macrostemonis Bulbus. Through network pharmacology and molecular docking, we identified five major active components of MFHF: Adenosine, Nonanoic Acid, Lauric Acid, Caprylic Acid, and Enanthic Acid, along with nine core targets (NFKB1, ALB, AKT1, ACTB, TNF, IL6, ESR1, CASP3, and PTGS) for the improvement of MVA. These 5 active components have various biological activities, such as reducing oxidative stress, anti-inflammation, analgesia effect, inhibiting platelet aggregation, vasodilatation, vascular endothelial protection, and cardio-protection. GO and KEGG enrichment analyses revealed that MFHF mainly acted on the response to xenobiotic stimulus, integrative component of the plasma membrane, RNA polymerase II transcription factor activity, ligand-activated sequence-specific DNA binding, pathways in cancer, lipid and atherosclerosis, human cytomegalovirus infection, and the PI3K-Akt signaling pathway, which are the main pathogenesis of MVA.

A Model for Predicting IoT User Behavior Based on Bayesian Learning and Neural Networks

To facilitate the allocation of energy and resources in the Internet of Things system, this paper presents a model for predicting user behavior in Internet of Things environments. The model is based on Bayesian learning and neural networks and is designed to provide insights into the future behavior of users, allowing for the allocation of resources in advance. In this paper, the data are preprocessed by data merging and format processing, and then the association rules are mined by association rules analysis. Finally, the data are utilized to train the behavioral prediction model of the short‐duration memory network via Bayesian optimization. The experimental results showed that the average running time of the research model was 1.682 s, the average accuracy was 96.77%, the average root‐mean‐square error was 0.382, and the average absolute error was 0.315. The designed behavior prediction model is capable of effectively predicting the user behavior of the Internet of Things, thereby enabling the reasonable allocation of energy and resources in the Internet of Things system.

An Apriori algorithm-based association rule analysis to identify acupoint combinations for treating uremic pruritus.

Uremic pruritus (UP) is a prevalent and troublesome condition affecting individuals with end-stage renal failure, which results in intense pruritus, depression, as well as poor quality of sleep, significantly impacting their quality of life. According to previous studies, acupuncture and acupoint stimulation have been shown to provide additional benefits in treating UP in dialysis patients. In addition, using acupoints combination may yield superior effectiveness compared to utilizing a singular acupoint. To investigate the potential correlations between acupoint combinations, an association-rule analysis was employed. Apriori algorithms stand out as highly potent techniques for identifying associations in databases; this study utilized an association rule mining to examine the association rules of key acupoint groupings that could be employed for treating UP. The analysis utilized information derived from the meta-analysis encompassing 40 randomized controlled trials that used acupuncture to treat UP. In total, 64 acupoints were analyzed, and 71 association rules were found. The following acupoint combinations: Auricular shenmen (TF4), Quchi (LI11), and Geshu (BL17); Auricular heart (Extra14), Sanyinjiao (SP6), and Auricular lung (CO14); and Auricular heart (Extra14), Xuehai (SP10), and Auricular lung (CO14) showed the strongest associations. Acupoints involving Auricular shenmen (TF4), Quchi (LI11), Geshu (BL17), Auricular heart (Extra14), Sanyinjiao (SP6), Auricular lung (CO14), and Xuehai (SP10) can be regarded as the core combination of acupuncture points for managing UP.

Eco-design modeling of home products in smart wellness environments

Abstract Intelligent recuperation mode represents a novel approach to elderly care, leveraging the capabilities of the Internet of Things (IoT) and big data. In this paper, based on the SOM-improved K-means algorithm, combined with association rule algorithm mining and analysis with time constraint factor, we establish an analysis model of elderly behavior recognition and make a preliminary judgment on the health status of older people based on the physiological parameters of the model. At the same time, an outlier detection algorithm based on normal distribution is being used to evaluate the abnormal behavior of elderly individuals and an intelligent recreational home ecosystem is being built and tested. In the evaluation of functional modules, except for the nutrition management and lighting control modules, which are rated as “average,” the evaluation values of the remaining eight modules are all in the range of [3,4], and their evaluation ratings are “good” and above. The evaluation values of all dimensions in the comprehensive evaluation of functions are all greater than 3, among which the evaluation values of the dimensions of perceived usefulness and tendency to use are 4.04 and 4.17, respectively, and the evaluation grade reaches the level of “excellent.” The average satisfaction value of the test experience is 3.77, which is 0.98 higher than the satisfaction value of using traditional household products.

Research on Teaching Quality Monitoring Mechanism of Colleges and Universities Based on Internet+Education Mode

Abstract This paper focuses on the “Internet + education” model and describes the feasible strategy of using data mining technology to establish a teaching quality monitoring mechanism in colleges and universities. Through the study of teaching quality monitoring pathways, such as teachers’ teaching level, students’ academic status, and course learning effectiveness, this paper’s main content provides a directional guide. Based on the teaching quality monitoring pathway, we choose the related algorithms of data mining technology, such as cluster analysis, association rule, and factor analysis, to be applied to the various aspects of the teaching quality monitoring pathway. The clustering algorithm is used to classify 1500 teachers in a university into 4 categories, such as excellent teaching effect, good teaching effect, etc., as well as to cluster students into 6 categories, such as excellent in all the courses and low to medium level, according to the course grades. In addition, this paper analyzes students’ course learning effectiveness, academic level, and career guidance using association rule algorithms, factor algorithms, and decision tree algorithms, respectively. From teachers’ teaching to students’ learning and employment, this paper constructs an all-round teaching quality monitoring mechanism using data mining technology, which contributes to the improvement of teaching quality in colleges and universities.

Xinfeng capsule inhibits lncRNA NONHSAT227927.1/TRAF2 to alleviate NF-κB-p65-induced immuno-inflammation in ankylosing spondylitis

Ethnopharmacological relevanceAnkylosing spondylitis (AS) is a chronic rheumatic disease known for its insidious and refractory symptoms, primarily associated with immuno-inflammation in its early stages, that affects the self-perception of patients (SPP). The exploration of long noncoding RNA (lncRNA) in immuno-inflammation of AS has garnered considerable interest. Additionally, the effectiveness of traditional Chinese medicine Xinfeng Capsule (XFC) in mitigating immuno-inflammation in AS has also been observed. However, the specific mechanisms still need to be characterized. Aim of the studyThis study elucidated the mechanism of the lncRNA NONHSAT227927.1/TRAF2/NF-κB axis in the immuno-inflammation of AS and XFC in AS treatment. MethodsLncRNA NONHSAT227927.1 and mRNA expression were assessed utilizing real-time fluorescence quantitative PCR. Protein level was determined using Western blot, and cytokine expression was measured using ELISA. Furthermore, mass spectrometry was used to analyze the binding proteins of lncRNA and rescue experiments were conducted to validate the findings. Inconsistencies in clinical baseline data were addressed using propensity score matching. The association between the XFC effect and indicator changes was evaluated using the Apriori algorithm. ResultsThe study revealed a substantial elevation in the expression of lncRNA NONHSAT227927.1 and tumor necrosis factor receptor-associated factor 2 (TRAF2) in AS-peripheral blood mononuclear cells. Its expression was also notably reduced after XFC treatment. In addition to this, there was a positive correlation between lncRNA NONHSAT227927.1 and TRAF2 with clinical immuno-inflammatory indicators. On the other hand, they showed a negative association with the SPP indicators. In vitro experiments have demonstrated that lncRNA NONHSAT227927.1 activated the nuclear factor (NF)-κB-p65 pathway by promoting TRAF2 expression. This activation resulted in enhanced IL-6 and TNF-α levels and reduced IL-10 and IL-4 levels. Conversely, XFC decreased the expression of lncRNA NONHSAT227927.1 and TRAF2, inhibiting the stimulation of the NF-κB-p65 cascade and restoring balance to the cytokines. The association rule analysis results indicated a strong association between XFC and decreased levels of C-reactive protein, erythrocyte sedimentation rate, and immunoglobulin A. Furthermore, XFC was strongly associated with improved SPP indicators, including general health, vitality, mental health, and role-emotional. ConclusionsLncRNA NONHSAT227927.1 plays a pro-inflammatory role in AS. XFC treatment may reverse lncRNA NONHSAT227927.1 to suppress TRAF2-mediated NF-κB-p65 activation, which in turn suppresses immuno-inflammation and improves SPP, thereby making XFC a promising candidate for therapeutic applications in AS management.

New Exploration on Tapping School History Resources to Empower the Teaching of Civics Classes in Colleges and Universities under the Perspective of Great Civics Classes

Abstract In this paper, in order to solve the teaching problems of college Civics courses under the perspective of the big Civics course, data mining technology is used to obtain school history resources and then construct research on the teaching of college Civics courses empowered by school history resources based on data mining. The initial data of school history resources obtained by data mining, regression analysis and decision tree analysis of the initial data are used to offset the influence of the attribute values of school history resources on the research results, and association rule analysis is used to help students understand the characteristics, connotation and connection between school history resources and the teaching of ideological and political education. Based on the relationship between school history resources and ideological and political education, a data mining-based research program on school history resources empowering ideological and political teaching was designed, confirmed and analyzed. The results show that the average scores of the four items of management attitude, management ability, management method and management effect in the school history resources empowering the teaching of ideology and politics are 0.6001, 0.5761, 0.5481, 0.5751, which indicates that the development of the school history resources based on mining association rule algorithms of data mining technology can better realize the function of teaching in the teaching of ideology and politics courses. This study enhances the use of previous school history resources in ideological and political education, which is conducive to the development of high-quality socialist successors and reliable builders.

Comorbidities in congenital heart disease: different patterns in childhood and adulthood

BackgroundExisting studies were no exploration of the association between congenital heart disease (CHD) in children and comorbidities. This study was to assess the prevalence and number of comorbidities in CHD among children and adults, and to compare the comorbidity patterns by children and adults using association rule analysis.MethodsPatients identified by the International Classification of Diseases, Ninth Revision (ICD‐9) code in the Medical Information Mart for Intensive Care III (MIMIC-III) 2001–2012 and MIMIC-IV 2008–2018 were included in this cross-sectional study. Association rule analysis was used to explore associations between CHD and comorbidities in children and adults using values of support (%), confidence (%), and lift.ResultsAmong 60,400 eligible patients, 1.54% of adults had CHD and 0.83% of adults had CHD with at least one comorbidity, 13.79% had CHD and 12.37% had CHD with at least one comorbidity in children. The most common comorbidities were circulatory system diseases (53.78%), endocrine diseases (35.76%), and respiratory system diseases (23.46%) in adults with CHD, and the most common comorbidities were perinatal diseases (87.50%) in children with CHD. The comorbidity rate was 90.19% and 56.68% in children and adults, respectively. In children, perinatal diseases, circulatory system diseases, and endocrine diseases had the highest prevalence. The incidence of circulatory system diseases, perinatal diseases and endocrine diseases in CHD adults was confidence = 31.56%, 36.11%, and 23.23%, respectively. Perinatal diseases were common comorbidities among all CHD severity groups in children and adults.ConclusionThe prevalence of comorbidities in children with CHD was higher than that in adults with CHD. The most common comorbidities were perinatal diseases and endocrine diseases among children and adults with CHD, respectively. Our study provided insights into comorbidity patterns in children and adults with CHD.

Medicine for chronic atrophic gastritis: a systematic review, meta- and network pharmacology analysis

Purpose The aim of this study is to determine the effectiveness and reliability of adding traditional Chinese medicine (TCM) in the clinical intervention and explore mechanisms of action for chronic atrophic gastritis (CAG) through meta- and network pharmacology analysis (NPAs). Methods A predefined search strategy was used to retrieve literature from PubMed, Embase database, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese BioMedical Literature Database (CBM), Wan Fang Data and China Science and Technology Journal Database (VIP). After applying inclusion and exclusion criteria, a total of 12 randomized controlled trials (RCTs) were included for meta-analysis to provide clinical evidence of the intervention effects. A network meta-analysis using Bayesian networks was conducted to observe the relative effects of different intervention measures and possible ranking of effects. The composition of the TCM formulation in the experimental group was analysed, and association rule mining was performed to identify hub herbal medicines. Target genes for CAG were searched in GeneCards, Online Mendelian Inheritance in Man, PharmGKB, Therapeutic Target Database and DrugBank. A regulatory network was constructed to connect the target genes with active ingredients of the hub herbal medicines. Enrichment analyses were performed using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to examine the central targets from a comprehensive viewpoint. Protein–protein interaction networks (PPINs) were constructed to identify hub genes and conduct molecular docking with differentially expressed genes (DEGs) and corresponding active molecules. Results A total of 1140 participants from 12 RCTs were included in the statistical analysis, confirming that the experimental group receiving the addition of TCM intervention had better clinical efficacy. Seven hub TCMs (Paeonia lactiflora, Atractylodes macrocephala, Pinellia ternata, Citrus reticulata, Codonopsis pilosula, Salvia miltiorrhiza and Coptis chinensis) were identified through association rule analysis of all included TCMs. Thirteen hub genes (CDKN1A, CASP3, STAT1, TP53, JUN, MAPK1, STAT3, MAPK3, MYC, HIF1A, FOS, MAPK14 and AKT1) were obtained from 90 gene PPINs. Differential gene expression analysis between the disease and normal gastric tissue identified MAPK1 and MAPK3 as the significant genes. Molecular docking analysis revealed that naringenin, luteolin and quercetin were the main active compounds with good binding activities to the two hub targets. GO analysis demonstrated the function of the targets in protein binding, while KEGG analysis indicated their involvement in important pathways related to cancer. Conclusions The results of a meta-analysis of 12 RCTs indicate that TCM intervention can improve the clinical treatment efficacy of CAG. NPAs identified seven hub TCM and 13 target genes associated with their actions, while bioinformatics analysis identified two DEGs between normal and CAG gastric tissues. Finally, molecular docking was employed to reveal the mechanism of action of the active molecules in TCM on the DEGs. These findings not only reveal the mechanisms of action of the active components of the TCMs, but also provide support for the development of new drugs, ultimately blocking the progression from chronic gastritis to gastric cancer.

Assessing Destination Brand Associations on Twitter: The case of Istanbul

The development of data mining has paved the way for studies that identify brand associations from user-generated content (UGC). However, the number of studies investigating destination associations with social media is limited. The aim of this study is to explore destination associations with UGC on Twitter and to show how data mining and sentiment analysis methods can be applied to destinations to elicit brand associations. In this study, 33,339 English-language tweets containing the word #Istanbul were collected over one year and analyzed using text mining (association rule analysis) and sentiment analysis. As a result of the study, a brand concept map (BCM) of what Twitter users associate with Istanbul was created and compared to other studies that measure associations using conventional methods. The main results show that users have positive associations with tourism in Istanbul. Unique and interesting associations (such as "cats") were observed compared to other previous studies that measured associations to destinations. Based on the study results, a method was proposed for measuring the image of a place brand by observing electronic word of mouth in social media.

Quantitative comparison on the similarities and differences of Mongolian medicines in the treatment of liver diseases between China and Mongolia based on data mining

Abstract Objective The R language was used to quantitatively compare the medication patterns of Mongolian medicines used for the treatment of liver diseases between China and Mongolia, with a view to provide a reference for the research and clinical application of Mongolian medicines in the treatment of liver diseases. Methods The Mongolian medicinal prescriptions used for treating liver disease in Mongolia were collected from the Mongolian Pharmacy and Mongolian Treatment Guide for Common diseases in Mongolian Medicine, and those used in China were collected from the Inner Mongolia Standard for Mongolian Proprietary Medicine and Annotation of Mongolian Medicine Preparation Specifications. After the database was established, the frequency, properties, and tastes of the Mongolian medicines were analyzed, and R studio was used for the association rules analysis and cluster analysis. Results A total of 27 prescriptions used in Inner Mongolia, China, were collected involving 105 Mongolian medicines, with a total frequency of 284. Among them, there were 18 high-frequency medicines (frequency ≥5), which had a frequency of 147, accounting for 51.76% of the total frequency. The medicine with the highest frequency (14, 4.93%) was Carthamus tinctorius L.. The analysis of the medicine data in China revealed 15 association rules. A total of 21 prescriptions used in Mongolia were collected, involving 92 Mongolian medicines, with a total frequency of 254. Among them, there were 17 high-frequency (frequency ≥5) medicines, with a total frequency of 124 (48.82%). The medicine with the highest frequency (13, 5.12%) was Carthamus tinctorius L.. The analysis of the medicine data in Mongolia revealed 79 association rules. In both regions, the high-frequency medicines used for treating liver disease commonly had cool or warm property with bitter or sweet taste. Conclusions Carthamus tinctorius L., Terminalia chebula Retz., and other Mongolian medicines are commonly used to treat liver diseases in Inner Mongolia and Mongolia. The Mongolian medicines with cool or warm property and bitter, sweet, or astringent taste are commonly used to protect the liver.

Study on Professor Diangui Li's Medication Experience in Treating Atrophic Gastritis Concomitant with Helicobacter Pylori Infection Based on Data Mining

Abstract Objective Our objective was to explore the national traditional Chinese medicine by studying master Diangui Li's medication experience in treating atrophic gastritis (AG) concomitant with Helicobacter pylori (Hp) infection based on data mining, and to provide the reference for the clinical treatment of relevant diseases. Methods The Chinese medicine prescriptions of the patients' first visits to the Famous Doctors' Consultation Room in Hebei Provincial Hospital of Chinese Medicine from May 2019 to December 2022 were collected and frequency analysis of the Chinese herbs, association rules analysis of the Chinese herbs, and cluster analysis were conducted using the Famous Doctor Inheritance Assistance Platform. Results A total of 188 prescriptions were collected, with 136 kinds of Chinese herbs. The highest use frequency of Chinese herbs was 185 and the lowest was 1. There were 28 kinds of Chinese herbs with high use frequency. The top 10 herbs with the high use frequency include Baihuasheshecao (Hedyotis Diffusae Herba), Huanglian (Coptidis Rhizoma), Yinchen (Artemisiae Scopariae Herba), Jigucao (Abriherba), Baishao (Paeoniae Radix Alba), Danggui (Angelicae Sinensis Radix), Banzhilian (Scutellariae Barbatae Herba), Baihe (Lilii Bulbus), Zhishi (Aurantii Immaturus Fructus), Chuanxiong (Chuanxiong Rhizoma). Chinese herbs with high frequency use are mostly heat-clearing herbs and qi-regulating herbs; the flavors of the herbs are mainly pungent, bitter, and sweet; the properties are mainly warm, cold, and neutral; the meridian tropism is mainly the spleen, liver, and stomach meridians. The core herbal medicines are Huanglian (Coptidis Rhizoma), Yinchen (Artemisiae Scopariae Herba), Baishao (Paeoniae Radix Alba), Danggui (Angelicae Sinensis Radix), etc.; the results of association rules: Jigucao (Abriherba)-Kushen (Sophorae Flavescentis Radix), Jiaogulan (Gynostemmatis Pentaphylli Rhizoma seu Herba)-Banlangen (Isatidis Radix), Huangqin (Scutellariae Radix)-Banlangen (Isatidis Radix), etc.; the results of cluster analysis showed that there were 10 clusters: (1) Yinchen (Artemisiae Scopariae Herba), Huanglian (Coptidis Rhizoma), Baihuasheshecao (Hedyotis Diffusae Herba), Banzhilian (Scutellariae Barbatae Herba), Jigucao (Abriherba); (2) Baishao (Paeoniae Radix Alba), Danggui (Angelicae Sinensis Radix), Chuanxiong (Chuanxiong Rhizoma), Wuyao (Linderae Radix); (3) Yuanhu (Corydalis Rhizoma), Danshen (Salviae Miltiorrhizae Radix et Rhizoma), Baizhi (Angelicae Dahuricae Radix). Conclusions For the treatment of AG concomitant with Hp infection, Professor Diangui Li mainly adopts the method of clearing heat and removing the toxin, regulating qi and resolving phlegm, combining disease differentiation with syndrome differentiation, performing reinforcing method, and reducing method simultaneously to regulate the mechanism of the human body.

Association Rules Analysis on Efficient Drug Offender Investigation Process Establishment

Association Rules Analysis on Efficient Drug Offender Investigation Process Establishment

On global maritime oil piracy: an association rules analysis

AbstractMaritime piracy is a global problem that disrupts oil flows and products. This research attempts to identify potential association rules between the features of hostile acts against tankers. To that end, the Apriori algorithm is used. We use data from the National Geospatial-Intelligence Agency and modify them in a basket case style. Essential features of an attack are examined, such as the closeness to the coasts, the cruising status of the tankers, and the time neighboring other attacks. Despite the perception we have of them, it turns out that pirates follow conservative strategies. It is found that success is strongly coupled with the safety of the attack by striking near the coast and on anchored tankers. The produced association rules include different time-neighboring conditions and no values regarding the attack month. This implies no strong preference for starting an attack, close or far from a previous episode, and no seasonality.

Prospects for the Application of Data Analysis Methods in the Evaluation of English Teaching in Colleges and Universities

Abstract This paper studies the specific application of association rule analysis in teaching evaluation in colleges and universities and analyzes the existing cases of the Apriori algorithm applied to college management under association rules. Aiming at the performance bottleneck of the Apriori algorithm in dealing with complex databases, the AMC algorithm based on matrix compression is proposed, and the data storage form is optimized through transaction matrix mapping. The improved AMC algorithm is applied to correlation analysis of English teaching evaluation data in colleges and universities, focusing on the correlation relationship between teaching characteristics, teaching-related factors, and evaluation grades based on confidence level. A confidence level of 69% will be achieved when the teaching effect is good, and the evaluation grade reaches basic satisfaction. A confidence level of 71% can be achieved when the teaching management is excellent and the evaluation grade is satisfactory.

A Study of Weathering and Classification Patterns of Glass Artifacts

Background: Ancient glass is very susceptible to the influence of the buried environment and weathering, in the weathering process, the internal elements of the glass and environmental elements for a large number of exchanges, resulting in a change in the proportion of its composition and thus affecting the correct judgment of its category.This paper discusses the identification of ancient glass artifacts (high-potassium glass and lead-barium glass) in relation to the effects of weathering, the statistics and patterns of content, and the study of issues related to the classification of types.
 Methods: The data were obtained from the data set of Question C of the 2022 Gaoxueshe Cup National University Student Mathematical Modeling Competition. After eliminating the invalid data, analytical methods such as association rule analysis, factor analysis, cluster analysis, and algorithms such as Apriori and K-means++ were used for problem solving.
 Results: A total of 56 glass artifacts and 56 artifact sampling sites were included in the study, and the main findings were as follows: the relationship between the weathering of the surface of glass objects and their glass type, decoration, and color under the two-, three-, and four-correlation rules; the classification of glass objects into high-potassium or lead-barium glass based on the five compositional categories (SiO2, PbO, CaO, Fe2O3, and K2O); and the clustered dendrograms. The most homogeneous classification of high-potassium or lead-barium glass into each of the three subcategories was based on magnesium oxide and aluminum oxide, whose content varied considerably before and after the weathering process; and finally, changes in the chemical compositional correlation between the different categories were also analyzed.
 Conclusion: Solved the problems related to the identification of the composition of this batch of ancient glass artifacts in relation to the effects of weathering, the statistics and patterns of the content, and the classification of the types.

Regularity of prescriptions for sick sinus syndrome based on latent structure combined with association rules

This study aims to mine the regularity of traditional Chinese medicine(TCM) prescriptions for sick sinus syndrome(SSS) and provide a reference for clinical syndrome differentiation and treatment. The relevant papers were retrieved from CNKI, Wanfang, VIP, and SinoMed with the time interval from inception to January 31, 2023. The relevant information from qualified papers was extracted to establish a library. Lantern 5.0 and Rstudio were used to analyze the latent structure and association rules of TCMs with the frequency ≥3%, which combined with frequency descriptions, were used to explore the rules of TCM prescriptions for SSS. A total of 192 TCM prescriptions were included, involving 115 TCMs with the cumulative frequency of 1 816. High-frequency TCMs include Aconiti Lateralis Radix Praeparata, Ginseng Radix et Rhizoma, Glycyrrhizae Radix et Rhizoma, Astragali Radix, and Salviae Miltiorrhizae Radix et Rhizoma. The high-frequency medicines mainly had the effects of tonifying, releasing exterior with pungent-warm, and activating blood and resolving stasis. The analysis of the latent structure model yielded 13 hidden variables, 26 hidden classes, 8 comprehensive cluster models, and 21 core prescriptions. Accordingly, the common syndromes of SSS were inferred as heart-Yang Qi deficiency, heart-spleen Yang deficiency, heart-kidney Yang deficiency, Yang deficiency and blood stasis, both Qi and Yin deficiency and blood stasis, and Yin and Yang deficiency. The analysis of association rules predicted 30 strong association rules, among which Ginseng Radix et Rhizoma-Aconiti Lateralis Radix Praeparata had the highest support. SSS is a syndrome with Yang deficiency and Qi deficiency as the root causes and cold, phlegm, and stasis as the manifestations. The clinical treatment of SSS should focus on warming Yang and replenishing Qi, which should be supplemented with the therapies of activating blood and resolving stasis, warming interior and dissipating cold, or regulating Qi movement for resolving phlegm according to the patients' syndromes.

Analysis of medication rules and application characteristics of Chinese patent medicine containing borneol based on data mining

BackgroundIn this study, the regularity of drug containing borneol proprietary Chinese medicine was mined, to provide reference for the clinical application and new drug research and development of borneol. MethodsThe database of proprietary Chinese medicines on Pharmaceutical Intelligence Network was searched for internal and external prescriptions that contained borneols and the diseases they treat. Microsoft Office Excel 2019 and SPSS Modeler 18.0 were used to analyze the properties, flavors, meridians tropisms and association rule analysis of the medicines, and Origin 21.0 software was used to draw the association rules diagram. ResultsAmong them, 528 prescriptions of internal Chinese patent medicine containing borneol and 387 prescriptions of external Chinese patent medicine were included. The diseases treated by internal prescription were mainly neurological diseases and heart diseases, among which Chinese medicines with higher frequency of compatibility with borneol were bezoar, licorice, cinnabar, musk and scutellaria. The diseases treated by external prescription were mainly physical disabilities, paralysis diseases, sore and ulcer diseases and so on. Among them, menthol, camphor, frankincense, angelica, and carthami flos and so on are the most frequently combined with borneol. ConclusionThe prescription of Chinese patent medicine containing borneol is composed of cold or warm, pungent or bitter Chinese medicine. Internal prescription primarily targets the meridians of the heart, liver, and lungs, and is often combined with sedative, antipyretic and detoxicating drugs to treat stroke, infantile convulsion and angina pectoris. External prescription mainly acts on liver, heart and spleen meridian, and is often combined with drugs for clearing heat, promoting blood circulation and removing blood stasis to treat rheumatic arthralgia syndrome and sore and ulcer diseases.

Can Online Consumer Reviews Identify Key Evidence Regarding Common Consumer Choices for High-Tech Pet Products?

Online consumer reviews (OCRs) significantly influence consumer purchase decisions for new products. Therefore, today’s companies actively seek practical approaches for analyzing these OCRs. This study proposes a comprehensive method for OCR analysis using topic modeling and association rule analysis to overcome the current limitations in topic interpretation and topic overlap in text mining. Meanwhile, to examine the development of the high-tech industry and customer interest in the pet care field, this study synthesizes and analyzes reviews from consumers who are using healthcare products in the pet industry. To this end, we first collected 20,820 customer reviews from Amazon.com (accessed on 2 August 2023) for high-tech pet products and categorized them into three distinct product categories. Topic modeling was then conducted on each category, revealing five key topics per category. Subsequently, association rules analysis was performed on the customer reviews associated with the most representative topic. As a result, we were able to demonstrate that ‘satisfaction’ emerged as the most crucial topic across all three categories of high-tech pet products. Satisfaction is a topic expressing consumers’ attitudes after experiencing the product, and they used words to describe their feelings in the product reviews. A diverse range of associated terms was also identified that represented the essence of each product’s corresponding representative explanations. By leveraging these approaches, we are confident that pet product companies and market players will gain valuable insights into consumer preferences and behavior.

Medication rules of Chinese herbal compound prescriptions for treating angina in national patent database based on multiple data mining

This study explored the medication rules of Chinese herbal compound prescriptions for the treatment of angina based on the Chinese herbal compound patents in the patent database of the China National Intellectual Property Administration. The data of eligible Chinese herbal compound patents for the treatment of angina were collected from the patent database of the China National Intellectual Property Administration from database inception to November 10, 2022, and subjected to data modeling, analysis of main syndromes, medication frequency analysis, cluster analysis, association rule analysis, and data visualization by using Excel 2021, IBM SPSS Statistics 26.0, IBM SPSS Modeler 18.0, Cytoscape 3.9.1, and Rstudio R 4.2.2.2 to explore the medication rules for angina. The study included 636 pieces of patent data for angina that met the inclusion criteria, involving 815 drugs, with a total frequency of 6 586. The most common main syndromes were blood stasis obstructing the heart syndrome(222, 34.91%) and Qi deficiency and blood stasis syndrome(112, 17.61%). The top 10 most frequently used drugs were Salviae Miltiorrhizae Radix et Rhizoma, Chuanxiong Rhizoma, Notoginseng Radix et Rhizoma, Astragali Radix, Angelicae Sinensis Radix, Carthami Flos, Glycyrrhizae Radix et Rhizoma, Ginseng Radix et Rhizoma, Borneolum Syntheticum, and Corydalis Rhizoma. High-frequency drugs included blood-activating and stasis-resolving drugs(1 197, 18.17%) and deficiency-tonifying drugs(809, 12.28%). Cluster analysis identified eight drug combinations, including five new prescriptions suitable for clinical use and new drug development, and three drug pairs. The core drug combination of Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma-Carthami Flos was identified through the complex co-occurrence network analysis of Chinese medicines. Association rule analysis yielded a total of 17 rules, including 13 drug pairs and 4 tripartite combinations. Common drug pairs included Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma(support degree 25.79%, confidence coefficient 69.49%, lift 1.30) and Salviae Miltiorrhizae Radix et Rhizoma-Notoginseng Radix et Rhizoma(support degree 22.01%, confidence coefficient 61.95%, lift 1.16). Common tripartite combinations included Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma-Astragali Radix(support degree 10.85%, confidence coefficient 73.40%, lift 1.37) and Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma-Notoginseng Radix et Rhizoma(support degree 10.69%, confidence coefficient 79.07%, lift 1.48). The results showed that the underlying pathogenesis of angina involved blood stasis obstructing the heart and Qi deficiency and blood stasis. The overall nature of the disease was characterized as asthenia in origin and sthenia in superficiality. In the prescription formulation, blood-activating and stasis-resolving drugs, such as Salviae Miltiorrhizae Radix et Rhizoma, Chuanxiong Rhizoma, and Carthami Flos were often used to resolve the excess manifestation, which were combined with tonifying drugs such as Astragali Radix, Angelicae Sinensis Radix, Glycyrrhizae Radix et Rhizoma, and Ginseng Radix et Rhizoma to reinforce the deficiency. The syndrome, pathogenesis, disease nature, and medication were consistent with clinical practice. Additionally, the new compound prescriptions and drug combinations derived from the multiple data mining in this study could provide references and insights for the clinical diagnosis and treatment of angina and the development of new drugs.