Application of data mining algorithms in research on traditional Chinese medicine formula / 中国药房

In recent years， data mining algorithms have been widely employed in scientific research within the field of traditional Chinese medicine （TCM）. The data mining algorithms are used to effectively handle and analyze the complex data in TCM formulas， providing a rational explanation for the mechanism of action. This method has proven particularly useful in uncovering patterns of compatibility and frequent combinations of herbs in TCM， thereby enhancing the reliability and accuracy of clinical diagnosis， target screening， and the study of new drugs. This paper reviews and analyzes 147 papers on TCM formula research that utilize data mining algorithms. The results indicate that data mining algorithms play a unique advantage in six sub- areas， including the study on the mechanism of action in TCM formula， the dose-efficacy of TCM formulas， the identification of core drugs pairs/groups， mining the relationships among “formulas-drug-symptom”， the discovery of new formulas， and mining the compatibility law. Notably， association rules and clustering algorithms are the most representative.

Application of Animal Models of Corneal Neovascularization Based on Data Mining / 中国实验方剂学杂志

ObjectiveTo provide a reference for the establishment of an ideal corneal neovascularization （CNV） animal model by summarizing the modeling characteristics of CNV animal models. MethodWith "CVN" as the theme word， this paper searched the China National Knowledge Infrastructure （CNKI）， Wanfang， Chinese medical journals full-text database， and PubMed database and screened out relevant literature on CNV animal experiments from 2013 to 2023. The database was established by Excel 2021， and the experimental animal strain， gender， modeling method， detection index， and application category were sorted out. The characteristics of the CNV animal model were analyzed. ResultAfter comparative analysis， it was found that the animal strains were Sprague-Dawley rats （87 times， 29.49%） and New Zealand white rabbits （52 times， 17.63%）. Male animals were recommended. Most modeling methods for efficacy verification and mechanism studies were the alkali burn method. Index detection methods included apparent index observation， histopathological detection， immunohistochemistry （IHC）， Western blot， and various polymerase chain reaction （PCR） tests. Detection indexes included apparent indication， corneal histopathology， CNV regulation， etc. ConclusionThe CNV model of SD rats induced by the alkali burn method is recommended for model replication， and the indexes are mainly selected from the growth of CNV， corneal histopathological test， and vascular endothelial growth factor （VEGF）-related test. In addition， according to the demand， the corneal apparent indication and the basic indexes related to the regulation of CNV， such as vascular endothelial growth factor receptor 2 （VEGFR2）， basic fibroblast growth factor （bFGF）， and secretogranin Ⅲ （Scg3） are also selected. Clinical treatment of CNV relies on anti-inflammatory drugs and anti-VEGF drugs， and there is a lack of application of traditional Chinese medicine （TCM）， so the model needs to be improved by adding elements of TCM syndromes.

Mining and analysis of acalabrutinib-induced ADE risk signals based on FDA adverse event reporting system / 中国药房

OBJECTIVE To provide reference for the clinically safe application of acalabrutinib by mining and analyzing the risk signals of adverse drug events （ADE）. METHODS The acalabrutinib-induced ADE reports were extracted from the U.S. FDA adverse event reporting system using the OpenVigil 2.1 platform from November 1， 2017 to March 31， 2023. The reporting odds ratio （ROR） method and composite criteria method from the Medicines and Healthcare Products Regulatory Agency （MHRA） were used for detection of ADE signals. RESULTS There were 7 869 ADE reports of acalabrutinib as the primary suspect drug and 142 ADE positive signals were detected from them， involving 20 system organ classes， which was generally consistent with the ADE recorded in the drug instruction of acalabrutinib， mainly involving general disorders and administration site conditions， various inspection， blood and lymphatic system disorders， various neurological disorders and cardiac disorders. In addition， this study identified several new potential ADE signals that were not mentioned in the drug instruction， including sudden cardiac death， pulmonary toxicity， tumor lysis syndrome， pleural effusion， dyspepsia， gastroesophageal reflux disease， bone pain， decreased blood pressure， and abnormal blood sodium， etc. CONCLUSIONS When using acalabrutinib， in addition to paying attention to the ADE recorded in its instructions， the risk of serious ADE that may lead to death， such as sudden cardiac death and pulmonary toxicity， should also be evaluated to avoid or reduce the occurrence of ADE as much as possible.

Análisis de interacciones de los actores de la red de conocimiento en salud ambiental del Observatorio Nacional de Salud de Colombia

Introducción: Las interrelaciones positivas y negativas entre el hombre y el medioambiente impactan en la salud general de la población, por esto, la gestión del conocimiento y la transformación social, orientadas a la prevención de la exposición a factores de riesgo ambiental y a la creación de ambientes propicios, deben realizarse a través de acciones multidisciplinares intersectoriales, como el trabajo colaborativo de redes del conocimiento. Objetivo: Describir las interacciones entre los actores de la Red de Conocimiento de Salud Ambiental del Observatorio Nacional de Salud de Colombia (ONS), con el fin de promover, mejorar y fortalecer la colaboración, intercambio de información y planificación conjunta de acciones. Metodología: Estudio descriptivo transversal de análisis de redes sociales mediante herramientas de minería de texto del lenguaje de programación R. Se analizaron las categorías de agua y saneamiento, clima, calidad del aire, radiaciones electromagnéticas e intoxicaciones químicas de un corpus documental de 99 textos de los actores de la red general de conocimiento en salud pública del ONS. Se calcularon medidas de centralidad y prestigio y se graficaron redes dirigidas multicapa con Power BI. Resultados: Los actores con mayor centralidad en la red fueron: Ministerio de Salud y Protección Social, Superintendencia de Salud, Profamilia, universidades de Antioquia y La Salle, ONS, Observatorio de Salud Ambiental de Bogotá, Organización Panamericana de la Salud y Organización Mundial de la Salud. Las cinco categorías analizadas presentaron bajas centralidades de grado, y las categorías de agua y clima mostraron mayor participación de los actores (más nodos e interacciones). Conclusiones: El análisis de redes sociales permitió identificar temas relevantes de salud ambiental entre los actores de la red del ONS, además de actores clave para desarrollar espacios de interacción y gestión del conocimiento. Acorde con las limitaciones del análisis, se sugiere la inclusión de aproximaciones bibliométricas para la actualización de las interacciones de la red.

Introduction: Positive and negative interactions between the human beings and the environment have an impact on the general health of the population. Therefore, it is necessary to use knowledge management and social transformation, in order to limit exposure to environmental risk factors by creating a favorable environment for healthcare. This should be carried out through multidisciplinary and intersectorial actions, such as the collaborative work of knowledge networks. Objective: To describe the interactions between the actors within the Environmental Health Knowledge Network Colombia's National Observatory of Health (ONS acronym in Spanish), in order to promote, improve and strengthen collaboration, information exchange and planning of collaborative actions. Methodology: Cross-sectional descriptive study to analyze social interactions through text mining tools by R, programmer language. Categories analyzed: Water and sanitation, climate, air quality, electromagnetic radiation and chemical poisoning. Data source: a documentary corpus of 99 texts done by actors of Environmental Health Knowledge Network of Colombia's ONS. We calculated centrality and prestige measures. We used Power BI in order to plot multi-layered directed networks. Results: Actors with greatest centrality in the network: Ministry of Health and Social Protection, Health Superintendency, Profamilia, Antioquia and La Salle universities, National Health Observatory, Bogota's Observatory of Environmental Health, the Pan American Health Organization and the World Health Organization. The five categories analyzed provides a low centrality degree, and water and climate categories presented greater participation by actors (more nodes and links). Conclusions: Social interactions analysis provides the identification of relevant environmental health issues in Colombia and key actors in order to develop interaction spaces for knowledge management. The analysis had limitations that suggest the inclusion of bibliometric approaches for updating the interactions within the network.

Modelo predictivo de enfermedad cardiovascular basado en inteligencia artificial en la atención primaria de salud / A Predictive Model for Cardiovascular Disease based on Artificial Intelligence in Primary Health Care

Introducción: En Cuba y en el resto del mundo, las enfermedades cardiovasculares son reconocidas como un problema de salud pública mayúsculo y creciente, que provoca una alta mortalidad. Objetivo: Diseñar un modelo predictivo para estimar el riesgo de enfermedad cardiovascular basado en técnicas de inteligencia artificial. Métodos: La fuente de datos fue una cohorte prospectiva que incluyó 1633 pacientes, seguidos durante 10 años, fue utilizada la herramienta de minería de datos Weka, se emplearon técnicas de selección de atributos para obtener un subconjunto más reducido de variables significativas, para generar los modelos fueron aplicados: el algoritmo de reglas JRip y el meta algoritmo Attribute Selected Classifier, usando como clasificadores el J48 y el Multilayer Perceptron. Se compararon los modelos obtenidos y se aplicaron las métricas más usadas para clases desbalanceadas. Resultados: El atributo más significativo fue el antecedente de hipertensión arterial, seguido por el colesterol de lipoproteínas de alta densidad y de baja densidad, la proteína c reactiva de alta sensibilidad y la tensión arterial sistólica, de estos atributos se derivaron todas las reglas de predicción, los algoritmos fueron efectivos para generar el modelo, el mejor desempeño fue con el Multilayer Perceptron, con una tasa de verdaderos positivos del 95,2 por ciento un área bajo la curva ROC de 0,987 en la validación cruzada. Conclusiones: Fue diseñado un modelo predictivo mediante técnicas de inteligencia artificial, lo que constituye un valioso recurso orientado a la prevención de las enfermedades cardiovasculares en la atención primaria de salud(AU)

Introduction: In Cuba and in the rest of the world, cardiovascular diseases are recognized as a major and growing public health problem, which causes high mortality. Objective: To design a predictive model to estimate the risk of cardiovascular disease based on artificial intelligence techniques. Methods: The data source was a prospective cohort including 1633 patients, followed for 10 years. The data mining tool Weka was used and attribute selection techniques were employed to obtain a smaller subset of significant variables. To generate the models, the rule algorithm JRip and the meta-algorithm Attribute Selected Classifier were applied, using J48 and Multilayer Perceptron as classifiers. The obtained models were compared and the most used metrics for unbalanced classes were applied. Results: The most significant attribute was history of arterial hypertension, followed by high and low density lipoprotein cholesterol, high sensitivity c-reactive protein and systolic blood pressure; all the prediction rules were derived from these attributes. The algorithms were effective to generate the model. The best performance was obtained using the Multilayer Perceptron, with a true positive rate of 95.2percent and an area under the ROC curve of 0.987 in the cross validation. Conclusions: A predictive model was designed using artificial intelligence techniques; it is a valuable resource oriented to the prevention of cardiovascular diseases in primary health care(AU)

Application of data mining to extract knowledge about the occurrence of fistulas after palatoplasty / Aplicação de mineração de dados para extração de conhecimento sobre ocorrência de fístulas após palatoplastia

Introduction: Data mining techniques expand access to important information for the decision-making process during health care. The objective the study proposes using data mining techniques to identify variables (surgical treatment protocols, patient characteristics, post-surgical complications) associated with fistulas after primary palatoplasty in patients with unilateral transforamen incisor cleft (UTIC). Method: A data set of 222 patients with UTIC without syndromes, operated by four surgeons with Furlow's or von Langenbeck's primary palatoplasty techniques, was analyzed for this study. Two models for detecting the outcome of surgery were induced using data mining techniques (Decision Tree and Apriori). Results: Five rules were selected from a decision tree pointing to some variables as predictors of fistulas associated with primary palatoplasty: infection, cough, hypernasality, and surgeon. Analysis of the model indicates that it correctly classifies 95.9% of occurrences between the absence and presence of fistulas. The second model indicates that the absence of post-surgical complications (infection and fever) and normal speech results (absent hypernasality, without suggestive of velopharyngeal dysfunction) are related to the absence of fistulas. Regarding surgical procedures, the Furlow technique and the Vomer flap were more frequent in patients with fistulas. Conclusion: Data mining techniques, as applied in the present study, pointed to infection and cough, hypernasality, and surgeon and surgical techniques as predictors of fistulas related to primary palatoplasty.

Introdução: As técnicas de mineração de dados ampliam o acesso a informações importantes para o processo de tomada de decisão durante os cuidados com a saúde. O objetivo do estudo propõe a utilização de técnicas de mineração de dados para identificar variáveis (protocolos de tratamento cirúrgico, características do paciente, intercorrências pós-cirúrgicas) associadas à ocorrência de fístulas após palatoplastia primária em pacientes com fissura transforame incisivo unilateral (FTIU). Método: Um conjunto de dados de 222 pacientes com FTIU sem síndromes, operados por quatro cirurgiões com as técnicas de palatoplastia primária de Furlow ou von Langenbeck, foi analisado para este estudo. Dois modelos para detecção do resultado da cirurgia foram induzidos usando técnicas de mineração de dados (Árvore de Decisão e Apriori). Resultados: Cinco regras foram selecionadas de uma árvore de decisão apontando para algumas variáveis como preditivas de fístulas associadas à palatoplastia primária: infecção, tosse, hipernasalidade, cirurgião. A análise do modelo indica que ele classifica corretamente 95,9% das ocorrências entre ausência e presença de fístulas. O segundo modelo indica que a ausência de intercorrências pós-cirúrgicas (infecção e febre) e resultado de fala normal (hipernasalidade ausente, sem sugestivo de disfunção velofaríngea) estão relacionados à ausência de fístulas. Em relação aos procedimentos cirúrgicos, o uso da técnica de Furlow e retalho de Vomer foram mais frequentes nos pacientes com fístulas. Conclusão: Técnicas de mineração de dados, conforme aplicadas no presente estudo, apontaram para infecção e tosse, presença de hipernasalidade, cirurgião e técnica cirúrgica como preditores de fístulas relacionadas à palatoplastia primária.

Forecasting The Risk Of Chronic Kidney Disease Using Artificial Intelligence Approaches

In this Paper With the aid of AI techniques, this study aims to predict the early detection of chronic kidney disease, also known as chronic renal disease, in diabetic patients. It then suggests a decision tree to reach specific conclusions with desired accuracy by evaluating its performance in relation to its specification and sensitivity. Methods: The behaviour of learning algorithms based on a set of data mining indicators affects the models that are produced proportionately. Predicting the future is no longer a difficult task thanks to the promises of predictive analytics in big data and the use of machine learning algorithms, especially for the health sector, which has undergone significant evolution as a result of the development of new computer technologies that gave rise to numerous fields of study research. Many initiatives are made to deal with the explosion of medical data on the one hand, and to learn meaningful information from it, forecast diseases, and anticipate treatments on the other. To extract meaningful information and aid in decision-making, researchers used all the technological advancements, including big data analytics, predictive analytics, machine learning, and learning algorithms.

Design of early warning system for mental health problems based on data mining and database / Projeto de sistema de alerta precoce para problemas de saúde mental com base na mineração de dados e banco de dados / Diseño de un sistema de alerta temprana de problemas de salud mental basado en la minería de datos y en la base de datos

ABSTRACT Introduction: Data mining technology is mainly employed in the era of big data to evaluate the acquired information. Subsequently, reasoning about the data inductively is fully automated to discover possible patterns. Objective: Recently, data mining technology in the national mental health database has deepened and can be effectively used to solve various mental health early warning problems. Methods: For example, it can be applied to mine psychological data and extract the most important features and information. Results: This paper presents the design of an early warning system for mental health problems based on data mining techniques to offer some thoughts on early warning of mental health problems, including data preparation, data mining, results in analysis, and decision tree algorithm. Conclusion: The experimental results indicate that the results of the early warning system in this paper can achieve an accuracy rate of more than 96% with a high accuracy rate. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

RESUMO Introdução: A tecnologia de mineração de dados é empregada principalmente na era da big data para avaliar as informações adquiridas. Posteriormente, raciocinar indutivamente sobre os dados de forma totalmente automatizada para descobrir possíveis padrões. Objetivo: Recentemente, a tecnologia de mineração de dados no banco de dados nacional de saúde mental tem se aprofundado e pode ser efetivamente utilizada para resolver vários problemas de alerta precoce da saúde mental. Métodos: Por exemplo, ela pode ser aplicada para a mineração de dados psicológicos e extrair as características e informações mais importantes. Resultados: Este documento apresenta o projeto de um sistema de alerta precoce para problemas de saúde mental baseado em técnicas de mineração de dados, com o objetivo de oferecer algumas reflexões sobre alerta precoce de problemas de saúde mental, incluindo preparação de dados, mineração de dados, análise de resultados e algoritmo de árvore de decisão. Conclusão: Os resultados experimentais indicam que os resultados do sistema de alerta precoce neste trabalho podem alcançar uma taxa de precisão de mais de 96% com uma alta taxa de precisão. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

Resumen Introducción: La tecnología de minería de datos se emplea principalmente en la era de la big data para evaluar la información adquirida. Posteriormente, razonar inductivamente sobre los datos de forma totalmente automatizada para descubrir posibles patrones. Objetivo: Recientemente, la tecnología de minería de datos en la base de datos nacional de salud mental se ha profundizado y puede ser utilizada eficazmente para resolver varios problemas de alerta temprana de salud mental. Métodos: Por ejemplo, puede aplicarse para minar datos psicológicos y extraer las características e información más importantes. Resultados: Este trabajo presenta el diseño de un sistema de alerta temprana de problemas de salud mental basado en técnicas de minería de datos, con el objetivo de ofrecer algunas reflexiones sobre la alerta temprana de problemas de salud mental, incluyendo la preparación de los datos, la minería de datos, el análisis de los resultados y el algoritmo de árbol de decisión. Conclusión: Los resultados experimentales indican que los resultados del sistema de alerta temprana de este documento pueden alcanzar un índice de precisión superior al 96% con un alto índice de precisión. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

Application analysis of digital neural network-based data mining method in maximizing the performance of sports training / Análise de aplicação do método de mineração de dados baseado em rede neural digital na maximização do desempenho do treinamento esportivo / Análisis de la aplicación del método de minería de datos basado en redes neuronales digitales para maximizar el rendimiento del entrenamiento deportivo

ABSTRACT Introduction: In today's rapid development of science and technology, digital network data mining technology is developing as fast as the expansion of the frontiers of science and technology allows, with a very broad application level, covering most of the civilized environment. However, there is still much to explore in the application of sports training. Objective: Analyze the feasibility of data mining based on the digital network of sports training, maximizing athletes' training. Methods: This paper uses the experimental analysis of human FFT, combined with BP artificial intelligence network and deep data mining technology, to design a new sports training environment. The controlled test of this model was designed to compare advanced athletic training modalities with traditional modalities, comparing the athletes' explosive power, endurance, and fitness. Results: After 30 days of physical training, the athletic strength of athletes with advanced fitness increased by 15.33%, endurance increased by 15.85%, and fitness increased by 14.23%. Conclusion: The algorithm designed in this paper positively impacts maximizing athletes' training. It may have a favorable impact on training outcomes, as well as increase the athlete's interest in the sport. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

RESUMO Introdução: No rápido desenvolvimento atual de ciência e tecnologia, a tecnologia de mineração de dados de rede digital desenvolve-se tão rápido quanto a expansão das fronteiras da ciência e tecnologia permitem, com um nível de aplicação muito amplo, cobrindo a maior parte do ambiente civilizado. No entanto, ainda há muito para explorar da aplicação no treinamento esportivo. Objetivo: Análise de viabilidade da mineração de dados com base na rede digital da formação esportiva, maximizar o treinamento dos atletas. Métodos: Este trabalho utiliza a análise experimental da FFT humana, combinada com a rede de inteligência artificial da BP e tecnologia de mineração profunda de dados, para projetar um novo ambiente de treinamento esportivo. O teste controlado deste modelo foi projetado para comparar modalidades avançadas de treinamento atlético com as modalidades tradicionais, comparando o poder explosivo, resistência e condição física do atleta. Resultados: Após 30 dias de treinamento físico, a força atlética dos esportistas com aptidão física avançada aumentou 15,33%, a resistência aumentou 15,85%, e o condicionamento físico aumentou 14,23%. Conclusão: O algoritmo desenhado neste artigo tem um impacto positivo na maximização do treinamento dos atletas. Pode ter um impacto favorável nos resultados do treinamento, bem como aumentar o interesse do atleta pelo esporte. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

RESUMEN Introducción: En el rápido desarrollo actual de la ciencia y la tecnología, la tecnología de extracción de datos de redes digitales se desarrolla tan rápido como lo permiten las fronteras en expansión de la ciencia y la tecnología, con un nivel de aplicación muy amplio que abarca la mayor parte del entorno civilizado. Sin embargo, aún queda mucho por explorar de la aplicación en el entrenamiento deportivo. Objetivo: Análisis de viabilidad de la minería de datos basada en la red digital de entrenamiento deportivo, maximizar la formación de los atletas. Métodos: Este trabajo utiliza el análisis experimental de la FFT humana, combinado con la red de inteligencia artificial BP y la tecnología de minería de datos profunda, para diseñar un nuevo entorno de entrenamiento deportivo. La prueba controlada de este modelo se diseñó para comparar las modalidades de entrenamiento atlético avanzado con las modalidades tradicionales, comparando la potencia explosiva, la resistencia y la forma física del atleta. Resultados: Después de 30 días de entrenamiento físico, la fuerza atlética de los atletas con un estado físico avanzado aumentó en un 15,33%, la resistencia aumentó en un 15,85% y el estado físico aumentó en un 14,23%. Conclusión: El algoritmo diseñado en este trabajo tiene un impacto positivo en la maximización del entrenamiento de los atletas. Puede tener un impacto favorable en los resultados del entrenamiento, así como aumentar el interés del atleta por el deporte. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

Evolution Patterns of 256 Cases of Chronic Kidney Disease with Kidney Yang Deficiency Syndrome Based on Data Mining / 中国实验方剂学杂志

ObjectiveTo analyze the characteristics of kidney Yang deficiency syndrome in different stages and time evolution of chronic kidney disease （CKD） to explore the evolution patterns of kidney Yang deficiency syndrome in CKD. MethodThe evidence information of 256 patients with CKD was collected from October 2020 to September 2022 according to relevant standards， and the "Kidney Yang Deficiency Syndrome Evaluation Scale for Chronic Kidney Disease" was developed. With SPSS Statistics 20.0， SPSS Modeler 18.0， Gephi 0.9.2， and R 4.2.1， the syndrome information of CKD patients at various stages and the syndrome changes after one year were statistically analyzed using complex network analysis， association rule analysis， probability transition matrix analysis， and chi-square test， and the kidney Yang deficiency syndrome of patients at various stages was comprehensively evaluated. ResultIn the CKD population， the proportion of females with kidney Yang deficiency syndrome was higher than that of males （P<0.01）， and the proportion of people over 65 years old was higher than in people under 65 years old. The proportion of people with kidney Yang deficiency syndrome increased with the progression of kidney disease， and the proportion of Ⅳ-Ⅴ CKD patients with kidney Yang deficiency syndrome was higher than that of Ⅰ-Ⅱ CKD patients （P<0.01）. From Ⅰ CKD to Ⅴ CKD， the frequency of dull tongue continued to increase， and the frequency of enlarged tongue and tooth-marked tongue continued to increase after Ⅲ CKD. The frequency of thick coating and greasy coating ranked in the top 3 of frequency distribution in Ⅴ CKD. After Ⅲ CKD， the top 3 tongue characteristics were weak pulse， deep pulse， and thready pulse， all of which were characteristics of kidney Yang deficiency syndrome. Complex network analysis of the tongue and pulse showed that the core tongue and pulse characteristics of patients with end-stage CKD were tooth-marked tongue with white coating and deep and thready pulse. The results of symptom frequency analysis and complex network analysis showed that aversion to cold and preference for warmth， weakness of the knees， and cold extremities were the top 3 symptoms in Ⅰ-Ⅲ CKD patients with kidney Yang deficiency syndrome， and in Ⅳ-Ⅴ CKD， the manifestations of the syndrome of Yang deficiency and water diffusion， such as drowsiness and fatigue， edema， and frequent urination at night became characteristic symptoms. The scores of edema， pale complexion， soreness and weakness of the waist and knees， loose stools， and mental depression symptoms， as well as the total score of kidney Yang deficiency syndrome gradually increased with disease progression， with statistical differences between different stages of CKD （P<0.05， P<0.01）. The frequency analysis of disease-related syndrome elements showed that the frequencies of Yang deficiency syndrome， phlegm-dampness syndrome， blood stasis syndrome， and turbidity-toxin syndrome gradually increased with disease progression， and there were statistically significant differences in the distribution between different stages of CKD （P<0.05， P<0.01）. The results of complex network analysis showed that Yang deficiency syndrome was the core syndrome element throughout all stages of CKD and was the main syndrome element type of CKD， while phlegm-dampness syndrome， blood stasis syndrome， and turbidity-toxin syndrome were gradually revealed in the middle and late stages of CKD. In the CKD population with kidney-Yang deficiency syndrome， the distribution of phlegm-dampness syndrome， blood stasis syndrome， and turbidity-toxin syndrome as concurrent syndromes in different CKD stages had statistically significant differences （P<0.05， P<0.01）. The association rule analysis showed that as the disease progressed， associations between the concurrent syndromes， such as phlegm-dampness syndrome， blood stasis syndrome， turbidity-toxin syndrome， and fluid retention syndrome， and kidney-Yang deficiency syndrome were gradually enhanced. The comparison of the changes in CKD with kidney Yang deficiency syndrome within one year showed that the disease location was centered on the kidney and transmitted between the spleen， stomach， heart， and liver. There is a 23.81% probability of kidney-Yang deficiency syndrome transforming into Qi deficiency syndromes （Qi deficiency in the spleen and kidney， Qi deficiency in the liver， and Qi deficiency in the heart）， 23.79% into Yin deficiency syndromes （Yin deficiency in the liver and kidney， Qi and Yin deficiency， and Yin deficiency in the liver and stomach）， and 9.52% into dampness syndromes （phlegm-dampness internal obstruction and wind-dampness obstruction）. In contrast， 20% of spleen and kidney Qi deficiency syndrome transformed into kidney Yang deficiency syndrome， and 33.33% of Qi deficiency and blood stasis syndrome transformed into kidney Yang deficiency syndrome. ConclusionAs Ⅰ CKD progresses to Ⅴ CKD， the severity of kidney Yang deficiency syndrome gradually increases， and the syndrome characteristics of kidney Yang deficiency become pronounced. Furthermore， the pathogenic factors， such as phlegm-dampness， blood stasis， and turbidity-toxin， gradually increase. With the change of time， kidney Yang deficiency syndrome in CKD tends to evolve into syndromes related to Qi deficiency， Yin deficiency， and dampness. The discovery of these rules provides a theoretical basis and reference guidance for the treatment of CKD based on syndrome differentiation.

Evaluation of Animal Models of Acute Lung Injury Caused by Non-physical Factors Based on Data Mining / 中国实验方剂学杂志

ObjectiveTo study the characteristics of animal models of acute lung injury caused by non-physical factors， so as to provide a reference for the standardization of the preparation of such animal models and lay a foundation for the research on the pathogenesis and the diagnosis and treatment of acute lung injury. MethodThe articles about the animal experiments of acute lung injury published in the last decade were retrieved from China National Knowledge Infrastructure （CNKI）， Wanfang， SinoMed， VIP， and PubMed with the theme terms of "acute lung injury" and "animal model". The animal species， drugs used in modeling， modeling period， methods used in molding， model standards， and model evaluation indicators were summarized， and Excel was used for the frequency analysis. ResultA total of 338 articles were included in this study. The results of the frequency analysis showed that SD rats/C57BL/6 mice were mainly used to establish the animal models of acute lung injury. Male mice were mostly used for modeling， and the commonly used modeling agent was lipopolysaccharides （LPS）. In most cases， the modeling lasted for 6 h after drug administration. Hematoxylin-eosin staining was mainly used for the observation of histological changes in the lungs， which were taken as the criteria for modeling. The established models were mainly evaluated based on lung dry/wet weight ratio， lung index， morphological changes in the lung tissue， myeloperoxidase （MPO）， superoxide dismutase （SOD）， and levels of inflammatory cytokines in the serum and bronchoalveolar lavage fluid （BALF）. ConclusionThe models of acute lung injury were mostly prepared by intraperitoneal injection of LPS （5 mg·kg-1） in SD rats and tracheal instillation of LPS （5 mg·kg-1） in C57BL/6 mice， which were praised for the simple operation， high success rate， and consistent with the pathogenesis of acute lung injury. This study provides a reference for the basic research on acute lung injury by animal experiments.

Research on Syndrome and Treatment Rules of Famous Doctors in Treating Ulcerative Colitis Based on Data Mining / 中医杂志

ObjectiveTo systematically review the clinical experience of four sessions of Masters of Traditional Chinese Medicine and two sessions of National Famous Chinese Medicine Practitioners in treating ulcerative colitis （UC）. Data mining and analysis were conducted to clarify the diagnosis and treatment ideas and characteristics of prescription used by these famous doctors in treating UC. MethodsRelevant literature on the treatment of UC by renowned doctors was retrieved from the establishment of the database until March 31， 2023. The literature was collected from databases such as China National Knowledge Infrastructure （CNKI）， Wanfang Data Knowledge Service Platform， Chinese Science and Technology Periodicals Database， and China Biomedical Literature Database. The data mining techniques including frequency analysis， association rules， and cluster analysis were conducted using the Ancient and Modern Medical Case Cloud Platform V2.3.5. ResultsA total of 157 literatures were included in this study， including 115 clinical case data. The study found that UC can be categorized into 14 types of syndrome patterns for treatment， including large intestine dampness-heat syndrome （75，65.22%）， syndrome of dampness stagnancy due to spleen deficiency （23， 20.00%）， spleen-kidney yang deficiency syndrome （21， 18.26%）. The main affected organs were the spleen （85， 73.91%） and large intestine （75， 65.22%）， and they were closely related to liver （24， 20.87%） and the kidney （21， 18.26%）. The predominant pathogenic factors were dampness （83， 72.17%） ， heat （80， 69.57%） and qi deficiency （65， 56.52%）. The treatment involved 30 kinds of treatment methods， including heat-clearing and dampness-draining method （75， 65.22%）， pleen-tonifying and qi-boosting method （25，21.74%） and spleen-invigorating and dampness-transforming method （23， 20.00%）. The medication involved 187 ingredients， with the most commonly used being heat-clearing herbs （37， 19.79%） and tonifying herbs （27， 14.44%）. The tastes of the herbs were mostly sweet （85， 45.45%） ， bitter （80， 42.78%） ， and pungent （71， 37.97%）. The association rules revealed 16 high-frequency combinations mainly composed of Huanglian （黄连）， Baishao （白芍） and Gancao （甘草） along with Baizhu （白术）， Fuling （茯苓）， Muxiang （木香） and Danggui （当归）. ConclusionFamous doctors are skilled in diagnosing and treating UC based on the differentiation of the zang-fu organs and qi-blood. The key pathological mechanism is “spleen deficiency as the root， and large intestine damp-heat as the manifestation”. The core treatment approach is “heat-clearing， spleen-tonifying， and dampness-draining”， with the inclusion of “regulating qi and blood， and balancing cold and heat”.

Research on the average age of onset of endometrial cancer based on data mining / 中国医师杂志

Objective:To explore the average age at onset of endometrial cancer (EC) and the differences between domestic and international factors.Methods:Pubmed, Wanfang Database, VIP Information Resource System, and China National Knowledge Infrastructure (CNKI) were selected to extract clinical research data related to EC. Through data mining methods such as frequency analysis and cluster analysis, we compared the differences in the average age of onset of EC between domestic and foreign countries.Results:A total of 280 articles that met the inclusion criteria were selected, and frequency analysis found that the average age of onset of EC in the Chinese population was mostly concentrated under 57 years old, while in European and American countries, it was mainly concentrated above 57 years old. Through cluster analysis, it was found that the average age of onset in China was clustered in one category with most Asian countries, while European and American countries and Australian countries were clustered in another category. Through analysis of domestic and foreign articles, it was found that the average age of onset of EC did not show a significant upward or downward trend with years.Conclusions:There are differences in the average onset age of EC among different countries and regions. The onset age of EC in Asian populations is significantly earlier than that in European and American populations. The average onset age of EC in Chinese populations is 54 years old, and there is no trend towards a younger onset of EC.

Analysis on medication rules of Xin'an medicine for treatment of melancholia administered by physicians in the Ming and Qing dynasties based on R language data mining / 中国基层医药

Objective:To investigate the medication rules of Xin'an medicine for the treatment of melancholia and further analyze the medication ideas of Xin'an physicians in the treatment of melancholia.Methods:The documents of Xin'an physicians treating melancholia in the fifth edition of the Chinese Medical Code and the online database of ancient Chinese medicine were retrieved. Excel was used to extract the prescription information to establish the database. R language was used to analyze the data regarding the medication frequency, nature and taste, association rules, and clustering of the traditional Chinese medicine used in the prescription. Results:A total of 127 effective prescriptions were sorted out, and 177 kinds of Chinese medicines were used with a total medication frequency of 1 031 times. The top three Chinese medicines with the highest frequency of use were Poria cocos (57 times), Licorice (46 times), and Paeonia Lactiflora (40 times). The main nature of herbs was plain and warm nature. The warm herbs were the most frequently used (298 times). The first five flavors of the herbs which were the most used were pungent taste (475 times, 28.70%), bitter taste (459 times, 27.73%), and sweet taste (453 times, 27.37%). The commonly used herbs with confidence coefficient > 0.800 were Licorice + Angelica sinensis, Licorice + Angelica sinensis and Paeonia Lactiflora, Licorice + Bupleurum, Licorice + Atractylodes macrocephala, Cyperus root + Ligusticum Chuanxiong, Angelica sinensis + Atractylodes macrocephala and Licorice, Paeonia Lactiflora + Angelica sinensis and Poria cocos, Licorice + Angelica sinensis and Poria cocos, Licorice + Atractylodes macrocephala and Angelica sinensis, Licorice + Bupleurum and Paeonia Lactiflora, Licorice + Atractylodes macrocephala and Ginseng, Licorice + Ginseng and Angelica sinensis, Cyperus root + Medicated leaven, Ginseng + Astragalus mongholicus, Licorice + Astragalus mongholicus.Conclusion:Xin'an medicine for the treatment of melancholia mainly uses pungent, bitter, sweet, and warm herbs. It can adjust the chill and fever, Yin and Yang of the human body, diminishes the urgency, and regulates the flow of Qi.

Research on the regulation of food therapy prescription of Traditional Chinese medicine in treating children′s stagnation based on data mining / 中国实用护理杂志

Objective:Data mining technology was used to analyze the regulation of food therapy prescriptions in treating children′s stagnation.Methods:Collect the therapy prescriptions used for regulating children's stagnation in the Dictionary of Traditional Chinese Medicine Prescriptions, the Complete Record of Dietary Therapy Prescriptions of Traditional Chinese Medicine and the Dictionary of Chinese Medicinal Diet, extract the information of prescription name, composition, etc, and use SPSS 22.0 for frequency analysis, and use Weka for correlation analysis. Results:A total of 99 dietary prescriptions for children with hysteria were included, involving a total of 62 foods, with a total use frequency of 224 times, among which the food with high use frequency were chicken gizzard, japonica rice, hawthorn, etc. The four characteristics of food were mainly concentrated in the flat, the five tastes were mainly concentrated in the sweet, the return channel was mainly concentrated in the spleen and stomach channel, and the effect was mainly concentrated in the absorption of food and tonic deficiency. The main symptoms of the therapeutic prescription for children's accumulation of stagnation were internal accumulation of milk and food and combination of spleen deficiency. The commonly used food combination for children's accumulation of stagnation of milk and food was "fructus amomi - chicken gizzard". The commonly used food combination of children with spleen deficiency and accumulation of stagnation was "lentil bean-yam-japonica rice" and "millet-yam".Conclusions:Traditional Chinese medicine diet prescription for the treatment of children's accumulation of stagnation pay attention to harmony and regulation, sweet and slow tonifying, emphasizing the adjustment of the spleen and stomach, taking into account the regulation of lung, following the "eliminating and supplementing both, according to the cause of treatment" rule, advocate syndrome differentiation of food.

Study on the law of syndrome differentiation and treatment about TCM for the treatment of type 2 diabetic kidney disease stage Ⅳ based on literature study / 国际中医中药杂志

Objective:To analyze the law of TCM syndrome differentiation and treatment for type 2 diabetic kidney disease (T2DKD) stage Ⅳ based on literature research.Methods:Literature on type 2 diabetic kidney disease stage Ⅳ was retrieved from CNKI, WanFang data, VIP and SinoMed database. The retrieval time was from the establishment of the databases to December 31, 2020. Data screening was conducted based on the inclusion and exclusion criteria prior to data entry in Microsoft Office Excel 365. Data mining and statistical analysis were performed by SPSS Statistics 23.0 and SPSS Modeler 18.1.Results:A total of 110 articles with 3 969 T2DKD stage Ⅳ cases, 111 prescriptions and 206 kinds of Chinese materia medica were included. Kidney and spleen were the main location of T2DKD stage Ⅳ. T2DKD stage Ⅳ based on TCM deficiency in nature syndrome was mainly based on qi and yin deficiency, and the most common excess in superficiality syndrome was blood stasis. The prescriptions commonly used included Liuwei Dihuang Decoction, Zhenwu Decoction, Buyang Huanwu Decoction, and Shenqi Dihuang Decoction etc. The classification of medication efficacy with the highest frequency was qi-tonifying herb, followed by blood-activating and stasis-resolving herb. Among them, Astragali Radix was the core Chinese materia medica in the prescription. The results of association rule obtained 54 association rules. Conclusions:The disease characteristics of T2DKD stage Ⅳ is simultaneous occurrence of deficiency and excess syndromes. The deficiency in nature is mainly characterized by deficiency of qi and yin, deficiency of spleen and kidney, deficiency of spleen-kidney yang, and excess in superficiality is mainly characterized by blood stasis, dampness and toxin. Tonifying qi and nourishing yin, activating blood circulation and dredging collaterals are the basic treatment methods, while strengthening spleen and kidney, dampness and detoxification should be emphasized. Astragali Radix, Angelicae Sinensis Radix, Salviae Miltiorrhizae Radix et Rhizoma, Poria, Dioscoreae Rhizoma, Corni Fructus, Rhei Radix et Rhizoma and Alismatis Rhizoma were the basic Chinese materia medica in this period, which reflects the idea of "treating qi, blood and water together".

Study on acupoint selection law of acupuncture for autism spectrum disorder based on data mining / 国际中医中药杂志

Objective:To analyze the acupoint selection law of acupuncture for autism spectrum disorder (ASD) using data mining techniques.Methods:Literature related to acupuncture for ASD was retrieved from the CNKI, SinoMed, VIP, Wanfang, and PubMed databases from the establishment of the databases to April 1, 2022, and then a database of acupuncture prescriptions was established. The frequency analysis of acupoint use was performed using Microsoft Excel 2019; the Apriori algorithm was used to analyze the association law of acupoints/acupoint areas; SPSS 26.0 was used to perform intergroup cluster analysis.Results:A total of 97 relevant articles with 97 acupuncture prescriptions and 98 acupoints/acupoint areas were included. The most frequently used acupoint was Shenmen (HT 7). The acupoint area of Jin's three-needle therapy and the Governor Vessel acupoints are commonly used. The most frequently occurring part of the acupoint/acupoint area was the head, and the most commonly used specific acupoint was the rendezvous acupoint. Association rule analysis yielded 40 groups of acupoints/acupoint areas, and the most commonly used combination was Laogong (PC 8) and Shenmen (HT 7). Four categories were extracted among high-frequency acupoints/acupoint areas by cluster analysis.Conclusion:Acupuncture treatment for ASD mainly selects the head acupoints, mainly selecting the acupoint area of Jin's three-needle therapy and the Governor Vessel acupoints, and paying attention to the use of specific acupoints.

Study on medication rule of TCM fumigation and washing in promoting the postoperative healing of hemorrhoids / 国际中医中药杂志

Objective:To analyze the medication law of Traditional Chinese Medicine (TCM) fumigation and washing to promote postoperative healing of hemorrhoids by data mining technology.Methods:The clinical literature about TCM fumigation and washing to promote postoperative healing of hemorrhoids was retrieved from the databases of CNKI, Wanfang, VIP, PubMed from the establishment of the databases to March 10, 2022. The frequency efficacy attributes, core medicinal pairs and core prescriptions of TCM were analyzed by using the Ancient and Modern Medical Records Cloud Platform (V2.3.5).Results:A total of 299 articles were included, involving 200 kinds of Chinese materia medica. The drugs used at high frequency ≥40 were Sophorae Flavescentis Radix, Phellodendri Chinensis Cortex, Natrii Sulfas, Galla Chinensis and Rhei Radix et Rhizoma and so on. The main efficacy was to clear heat and reduce dampness; cold, warm and slightly cold were the main medicinal properties, and the tastes were mainly bitter, pungent, sweet and sour, and most of the drugs return to the liver meridian, stomach meridian, heart meridian, large intestine meridian and so on. A total of 22 rules were obtained by correlation analysis. Five groups of drugs were obtained by clustering analysis. The core prescription drugs obtained by complex network analysis included Sophorae Flavescentis Radix, Phellodendri Chinensis Cortex, Natrii Sulfas, Galla Chinensis, Rhei Radix et Rhizoma, Taraxaci Herba, Borneolum Syntheticum, Sanguisorbae Radix, Atractylodis Rhizoma, Carthami Flos, Scutellariae Radix, Olibanum, Myrrha, and Lonicerae Japonicae Flos. Conclusion:TCM fumigation and washing can promote the postoperative healing of hemorrhoids mainly by clearing heat and reducing dampness and detoxification, as well as promoting blood circulation and removing blood stasis, reducing swelling and relieving pain, restraining sore and generating muscle.

Study on medication law of TCM compounds for treatment of blood stasis type vascular dementia / 国际中医中药杂志

Objective:To explore the medication law and core Traditional Chinese Medicine (TCM) compounds in the treatment of blood stasis vascular dementia (VD) based on data mining.Methods:The literature about TCM treatment for blood stasis VD was retrieved from the databases of CNKI, Wanfang, VIP, and CBM from January 2000 to November 2021. Microsoft Office Excel 2019, SPSS Modeler 18.0, SPSS Statistics 25.0, R X64 4.1.2, and Origin 2021 were used to perform medication frequency analysis, frequency analysis of four properties and five tastes of TCM, association rules, clustering analysis, factor analysis and data visualization.Results:A total of 196 articles were included, with 196 TCM prescriptions, involving 200 kinds of Chinese materia medica. High-frequency drugs were for Acori Tatarinowii Rhizoma, Chuanxiong Rhizoma, Salviae Miltiorrhizae Radix et Rhizoma, Polygalae Radix, Carthami Flos. The medicinal properties were mainly warm, mild and cold, the tastes were mainly sweet, bitter and pungent, and the meridians were mainly liver meridian, spleen meridian and heart meridian. A total of 19 association rules were obtained from the analysis of association rules for 2 kinds of Chinese materia medica, and the rules of the representative were Acori Tatarinowii Rhizoma- Polygalae Radix, Chuanxiong Rhizoma- Carthami Flos, Acori Tatarinowii Rhizoma- Curcumae Radix. A total of 4 categories were extracted through clustering analysis. Factor analysis extracted a total of 8 common factors. Conclusion:The core pathogenesis of blood stasis VD is blood stasis blocking brain collaterals, and there were also pathological factors such as qi deficiency, yin deficiency, phlegm turbidity and so on. The basic treatment is promoting blood circulation and removing stasis, and different methods of promoting blood circulation and drugs are selected. The methods of strengthening spleen and reducing phlegm, nourishing yin and blood, inducing resuscitation, tonifying the kidney and spleen, regulating qi, promoting collaterals and so on can also be used based on syndromes and symptoms of the patients.

Study on medication law of TCM compounds with national patents for treatment of vascular dementia / 国际中医中药杂志

Objective:To explore the prescription and medication law of Traditional Chinese Medicine (TCM) compounds in the treatment of vascular dementia (VD) based on patent database.Methods:TCM compounds with patents about VD were retrieved from Chinese patent announcement website of the State Intellectual Property Office and CNKI. The retrieval time was from the establishment to the databases to 31 st, March 2022. The frequency, clusteringand association analysis were carried out with the help of TCM inheritance auxiliary platform (V2.5). The medication law was analyzed. Results:154 TCM compound patents for the treatment of vascular dementia were screened, involving 227 kinds of Chinese materia medica. Among them, Acori Tatarinowii Rhizoma (44 times, 28.57%) was used more frequently, and the common medicinal pair was Salviea Miltiorrhizae Radix et Rhizoma- Acori Tatarinowii Rhizoma (17 times, 11.03%). The medicinal property was mainly warm, the taste was mainly sweet, and the meridian was mainly liver meridian. Those with high confidence based on association rules were " Corni Fructus -Acori Tatarinowii Rhizoma" (0.90), " Corni Fructus -Rehmannize Radix et Praeparata" (0.90). Based on the complex network, it was concluded that the core drugs were 14 groups such as " Rehmannize Radix et Praeparata- Cistanches Herba- Corni Fructus". The new prescriptions extracted by entropy cluster analysis included 7 groups such as " Rehmannize Radix et Praeparata, Cistanches Herba, Corni Fructus and Asparagi Radix". Conclusion:The treatment of VD by TCM compounds with national patents is mainly based on tonifying deficiency, promoting blood circulation and removing blood stasis, eliminating phlegm and dampness, expelling wind and dredging collaterals, opening orifices and resuscitation, which can provide reference for clinical practice and new drug research and development.