A Preliminary Study on the Construction and Visualization of Knowledge Graph for the Ancient Chinese Medical Book Ling Shu / 广州中医药大学学报

Objective To explore the construction and visualization for knowledge graph of Ling Shu(Spiritual Pivot),with a view to providing ideas for the structured storage and display of the theoretical knowledge of the ancient Chinese medical books.Methods Using the professional idea of constructing knowledge graphs for reference,text mining technology was applied to construct the thesaurus,and then word division,entity recognition,and relationship extraction for the original text of Ling Shu were performed to get the elements of knowledge graph construction.The graph database Neo4j was used for the storage and query of the knowledge graph,and then the visual display of the knowledge graph was achieved.Results The 1 216 high-quality words consisting of the thesaurus of Ling Shu were obtained,and the construction of the knowledge graph of the theory of Ling Shu was realized.The constructed knowledge graph basically displayed the traditional Chinese medicine theories such as the correlation of visceral manifestations with essence qi,and the relationship between emotions and the five-zang organs described in Ling Shu,which made the retrieval and utilization of the related entities and relationships possible,and provided ideas for the structured storage and display of the theoretical knowledge of the ancient books of Chinese medicine.Conclusion The knowledge graph construction technology can be used to obtain the Chinese medicine theoretical knowledge graph of Ling Shu,and to display the knowledge connections of yin-yang and the five elements,and the internal organs and meridians expressed in the Ling Shu.The construction of the knowledge graph and its storage in the graph database enable the knowledge graph involved in the text of Ling Shu to be displayed in the form of visualized semantic network graph,and also make the embedding of other search systems such as the semantic search and semantic wiki possible,which will be helpful for the development of Chinese medicine intelligent medical services.

Bibliometric and visual analysis of domestic and foreign scoliosis orthoses / 中国组织工程研究

BACKGROUND:Scoliosis mainly refers to sequence abnormalities in the coronal,sagittal,and axial positions of the spine,with a Cobb angle of≥10°.The patients may experience symptoms such as unequal shoulder height and back asymmetry.Severe cases may affect the patient's cardiopulmonary function,thereby affecting their daily life.Conservative treatment can control the progression of scoliosis and avoid later surgery.Scoliosis orthosis is currently a commonly used and effective treatment measure in conservative treatment. OBJECTIVE:To summarize and analyze the current research status,hotspots,and trends of scoliosis orthoses both domestically and internationally,providing reference for related research. METHODS:Using bibliometrics and visual analysis as tools,and using a comparison between China and foreign countries as a method,this paper analyzes the literature on scoliosis orthosis journals in the past decade.Based on bibliometrics,the current status of research on scoliosis orthoses is determined.Citespace software is used to analyze key words and identify the current hotspots and future trends in scoliosis orthosis research. RESULTS AND CONCLUSION:(1)At present,the number of literature on scoliosis orthoses is still on a fluctuating upward trend.China and the United States are the main countries for research,with a literature share of over 40%.However,the average citation rate of foreign language literature by Chinese scholars is relatively low.(2)The basic fields of domestic research are mainly surgery and pediatrics,while orthotics and clinical neurology are mainly studied abroad.Among them,there is also a certain number of documents in domestic Chinese medicine,indicating that China is also engaged in the combination of Chinese and Western treatment of scoliosis.The National Natural Science Foundation of China has the highest proportion in the aspect of Chinese and foreign literature,reflecting the importance of the fund attaches to the research of scoliosis orthosis.(3)The authors with the highest number of publications are Qiu Yong and Negrini Stefano,and the most published institutions are the Spinal Surgery Department of Gulou Hospital affiliated to Nanjing University Medical College and UDICE-French Research University.Domestic and foreign authors and institutions have certain communications about this,but not closely,which requires relevant institutions and scholars to further explore and study.(4)From the research hotspots and future trends,the main treatment type is adolescent idiopathic scoliosis,while the production method of the short-column side bending orthosis is three-dimensinoal printing,and the main treatment index is convex progression.The ultimate purpose of treatment is to improve the quality of life of the patients.

Knowledge graph and future prospects of medical security research:literature analysis based on CNKI(since 1998) / 现代医院

Objective To present a knowledge graph of over 20 years of research on medical security and predict future trends.Methods Based on 4818 Chinese core journal papers indexed by CNKI since 1998,CiteSpace 5.0 was used to present a knowledge graph of medical security research from three aspects:time zone distribution,force composition,and research con-tent.Results Medical security research has gone through three stages:the initial stage,the peak stage,and the adjustment and stability stage.At present,the development of research forces is uneven,and the cooperation network shows a trend of partial concentration and overall dispersion.The research topics focus on seven aspects such as the construction of medical security sys-tem,internal design of the system,external support system,and new rural cooperative medical care.Conclusion In the future,efforts should be made to build a research system for medical security governance and highlight the innovation and development of legal construction of medical security in five aspects.

Construction and Application of Clinical Experience Knowledge Graph for Renowned TCM Doctors in Treating Coronary Heart Disease / 中国中医药信息杂志

Objective To build a knowledge graph;To visualize the knowledge structure relationships and clinical thinking in the treatment of coronary heart disease by renowned TCM doctors;To provide methodological reference for the inheritance of experience of renowned TCM doctors.Methods Medical records about treatment of coronary heart disease by renowned TCM doctors were retrieved from CNKI from the establishment of the database to 30th,Nov.2022.The characteristics of TCM diagnosis and treatment and the characteristics of the theoretical system of syndrome differentiation and treatment in TCM were analyzed.Concept types and relationships between concepts were sorted out and extracted to form a pattern layer of knowledge graph;based on the characteristics of the pattern layer,Python 3.11(PyCharm 2022.3.2)was used to write rules,and knowledge extraction and data import were implemented through the Pandas library,Openpyxl library and Py2neo library,which were stored in the graph database Neo4j-Community-5.2.0 to complete the construction of the knowledge graph.Implementing query application was realized through Cypher language.Results The data of 643 medical cases of 144 renowned TCM doctors were included,which were entered into the Neo4j graph database,forming a knowledge graph consisting of 2 744 nodes and 23 795 relationships under 8 concepts and 10 relationships,to achieve visual presentation and query application of the diagnosis and treatment process of coronary heart disease by renowned TCM doctors.Conclusion The knowledge graph can intuitively display the relationship of diseases-symptoms-syndromes-treatments-prescriptions-medicine in medical records,develop a knowledge system that is easy to retrieve,and improve the accessibility of domain knowledge,which can provide methodological reference for the inheritance of experience of renowned TCM doctors.

Construction of domain knowledge graph of dementia care / 中华护理杂志

Objective To construct a domain knowledge graph of dementia care,so as to provide the foundation and guarantee for the next intelligent application based on the knowledge graph.Methods A top-down approach was adopted to construct a domain knowledge graph of dementia care.Firstly,the ontology concept is constructed from the top level,namely the schema layer of knowledge graph.Then,instances are filled,and knowledge extraction is carried out from the existing data sources,and the extracted entities and relationships are filled into the pattern layer ontology database to complete the data layer construction of the knowledge graph.Finally,the"entity relationship entity"triplet data was input into the Neo4j graph database for storage.Results In this study,the personalized care plan set of 1 012 dementia cases was used as the corpus to construct a domain knowledge graph of dementia care.The knowledge graph takes people with dementia as the core,and unfolds,one by one,around basic characteristics,care problems,and care plans in a standardized"entity-relationship-entity"triplet format,forming a large knowledge network,which contains a total of 1 522 specific dementia care knowledge entities and 8 kinds of inter-entity relationships.Conclusion The domain knowledge graph of dementia care constructed in this study clearly and intuitively shows the global pedigree and logical path of knowledge,which provides an efficient and intelligent basic guarantee for the browsing,retrieval and application of dementia care knowledge,so as to realize personalized and intelligent management of people with dementia,break through the bottleneck of lack of professionals,improve the health outcomes of people with dementia,promote the implementation of inclusive pension services,and promote healthy aging.

Intelligent question answering system for traditional Chinese medicine based on BSG deep learning model: taking prescription and Chinese materia medica as examples / 数字中医药（英文）

Objective @#To construct a traditional Chinese medicine (TCM) knowledge base using knowledge graph based on deep learning methods, and to explore the application of joint models in intelligent question answering systems for TCM.@*Methods@#Textbooks Prescriptions of Chinese Materia Medica and Chinese Materia Medica were applied to construct a comprehensive knowledge graph serving as the foundation for the intelligent question answering system. In the study, a BERT+Slot-Gated (BSG) deep learning model was applied for the identification of TCM entities and question intentions presented by users in their questions. Answers retrieved from the knowledge graph based on the identified entities and intentions were then returned to the user. The Flask framework and BSG model were utilized to develop the intelligent question answering system of TCM.@*Result@#A TCM knowledge map encompassing 3 149 entities and 6 891 relational triples based on the prescriptions and Chinese materia medica was drawn. In the question answering test assisted by a question corpus, the F1 value for recognizing entities when answering 20 types of TCM questions was 0.996 9, and the accuracy rate for identifying intentions was 99.75%. This indicates that the system is both feasible and practical. Users can interact with the system through the WeChat Official Account platform.@*Conclusion@#The BSG model proposed in this paper achieved good results in experiments by increasing the vector dimension, indicating the effectiveness of the joint model method and providing new research ideas for the implementation of intelligent question answering systems in TCM.

Construction of Knowledge Graph Based on Literature Data by Taking Treatment of Diabetic Peripheral Neuropathy with Traditional Chinese Medicine as An Example / 中国实验方剂学杂志

ObjectiveTo systematically sort out the knowledge framework and conceptual logic relationship of "disease-syndrome-treatment-prescription-medicine" in the existing literature on traditional Chinese medicine（TCM） treatment of diabetic peripheral neuropathy（DPN）， to construct of the knowledge map of TCM treatment of DPN， and to promote the explicitation of the implicit knowledge in the literature on the treatment of DPN with TCM. MethodTaking the literature of China National Knowledge Infrastructure about TCM treatment of DPN as the main data source， TCM-related concepts and entities were constructed by manual citation， and the corresponding relationships between the entities were established. Structured data were formed by processing with Python 3.7， and the knowledge graph was constructed based on Neo4j 3.5.34 graph database. ResultThe resulting knowledge graph with TCM diagnosis and treatment logic， defined 12 node labels such as prescriptions， Chinese medicines and syndrome types at the schema layer， as well as 4 types of relationships， such as inclusion， correspondence， selection and composition. It could support the query and discovery of nodes（syndrome elements， syndrome types and treatment methods）， as well as the relationship between each node. ConclusionBased on the literature data， this study constructed a knowledge map for TCM treatment of DPN， which brought together various methods of TCM treatment of DPN， including internal and external treatment. The whole chain knowledge structure of syndrome differentiation and classification for DPN treatment is formed from syndrome element analysis， syndrome type composition to treatment method selection， which can provide new ideas and methods for literature data to serve clinical and scientific research work， as well as reference for visualization of TCM literature knowledge， intellectualization of TCM knowledge services and the standardization of TCM diagnosis and treatment.

Knowledge Graph Enhanced Transformers for Diagnosis Generation of Chinese Medicine / 中国结合医学杂志

Chinese medicine (CM) diagnosis intellectualization is one of the hotspots in the research of CM modernization. The traditional CM intelligent diagnosis models transform the CM diagnosis issues into classification issues, however, it is difficult to solve the problems such as excessive or similar categories. With the development of natural language processing techniques, text generation technique has become increasingly mature. In this study, we aimed to establish the CM diagnosis generation model by transforming the CM diagnosis issues into text generation issues. The semantic context characteristic learning capacity was enhanced referring to Bidirectional Long Short-Term Memory (BILSTM) with Transformer as the backbone network. Meanwhile, the CM diagnosis generation model Knowledge Graph Enhanced Transformer (KGET) was established by introducing the knowledge in medical field to enhance the inferential capability. The KGET model was established based on 566 CM case texts, and was compared with the classic text generation models including Long Short-Term Memory sequence-to-sequence (LSTM-seq2seq), Bidirectional and Auto-Regression Transformer (BART), and Chinese Pre-trained Unbalanced Transformer (CPT), so as to analyze the model manifestations. Finally, the ablation experiments were performed to explore the influence of the optimized part on the KGET model. The results of Bilingual Evaluation Understudy (BLEU), Recall-Oriented Understudy for Gisting Evaluation 1 (ROUGE1), ROUGE2 and Edit distance of KGET model were 45.85, 73.93, 54.59 and 7.12, respectively in this study. Compared with LSTM-seq2seq, BART and CPT models, the KGET model was higher in BLEU, ROUGE1 and ROUGE2 by 6.00-17.09, 1.65-9.39 and 0.51-17.62, respectively, and lower in Edit distance by 0.47-3.21. The ablation experiment results revealed that introduction of BILSTM model and prior knowledge could significantly increase the model performance. Additionally, the manual assessment indicated that the CM diagnosis results of the KGET model used in this study were highly consistent with the practical diagnosis results. In conclusion, text generation technology can be effectively applied to CM diagnostic modeling. It can effectively avoid the problem of poor diagnostic performance caused by excessive and similar categories in traditional CM diagnostic classification models. CM diagnostic text generation technology has broad application prospects in the future.

Applications of Intelligent Governance in the Health Field from the Perspective of Sociology——Taking Peking University Third Hospital as an Example / 医学信息学杂志

Purpose/Significance To conduct the real world research on the application and impact of artificial intelligence(AI)technology in medical institutions,and to assist in intelligent governance decision-making in the field of medicine and health.Method/Process Taking Peking University Third Hospital as the research scene,the AI medical social experiment is carried out through literature meta-analysis,knowledge graph construction and mixed methodology research.Result/Conclusion Scholars at home and abroad are cautious and optimistic about the application of AI technology in the field of health.The research,development and application of AI technology in domestic public hospitals are very active,but small-scale field studies suggest that AI technology may lead to problems such as misleading decision-making and weakening of human subjectivity while improving the efficiency of diagnosis and treatment.In-telligent governance in the field of health,represented by AI technology,requires a long period and a wide range of sociological observa-tions.It is recommended to build a research base for medical AI technology R&D and supervision based on public hospitals,and continue to pay attention to issues such as human subjectivity,medical ethics and scientific and technological ethics in AI social governance.

A Review of the Knowledge Discovery Methods Based on Knowledge Graph in the Biomedical Field / 医学信息学杂志

Purpose/Significance To review the knowledge discovery methods based on knowledge graph in the biomedical field,and to provide references for researchers.Methods/Process The paper summarizes the knowledge discovery methods based on knowledge graph by systematically searching and analyzing the relevant literatures,and compares the advantages and disadvantages of various knowl-edge discovery methods.It points out that the limitations and challenges of knowledge discovery methods based on knowledge graph in the biomedical field,and puts forward suggestions and prospects.Result/Conclusion In the future research,it is suggested to improve the in-terpretability of knowledge discovery results,build an effective result evaluation framework,and establish a standardized knowledge dis-covery process with multi-domain experts'collaboration,so as to improve the quality and efficiency of knowledge discovery research.

Research Progress and Future Prospect of Health Recommender System / 医学信息学杂志

Purpose/Significance To explore the research progress of health recommender system(HRS),so as to provide refer-ences for medical personnel to build HRS to help intelligent health care.Method/Process The application of common recommendation technology and HRS in the field of health care is summarized by literature research,and the research status and development direction of HRS is discussed.Result/Conclusion HRS has been applied in health service recommendation,diet recommendation,health behavior promotion,disease prognosis characteristics and health risk prediction,chronic disease management,mental health promotion and medi-cation recommendation,and the related research is conducive to the development of intelligent health care.

Based on CiteSpace Visualization Analysis of TCM Treatment of Chronic Obstructive Pulmonary Disease / 医学研究杂志

Objective To explore the hot topics and the research trend of traditional Chinese medicine treatment of chronic obstruc-tive pulmonary disease in 2017-2021,and to aware the cooperation among authors and institutions in the field.Methods Literature on TCM treatment of chronic obstructive pulmonary disease published in CNKI and PubMed in 2017-2021 was searched,and CiteSpace 5.8 R3 was used to visualize the authors,research institutions and keywords of the included literatures.Results A total of 3082 Chinese literatures and 1093 English literatures were included.In 2017-2021,the trend of publication has always shown a steady growth,and there was a lack of communication and cooperation among authors and teams.Keywords visualization map showed 18 clusters and 20 emer-gent words.Conclusion Traditional Chinese medicine treatment of chronic obstructive pulmonary disease is mainly focused on syndrome type,treatment methods,disease mechanism and related curative effect indicators,and the syndrome differentiation analysis and clinical curative effect evaluation of traditional Chinese medicine compounds are still the main forces at present.As the patients quality of life is becoming more and more attention,how to strengthen pulmonary rehabilitation education,improve patient compliance,and expand the lo-cation and area of pulmonary rehabilitation is one of the current research trends.

Diagnosis and Treatment Reasoning of Integrated Traditional Chinese and Western Medicine Against Acute Abdomen Based on Knowledge Graph / 中国实验方剂学杂志

ObjectiveIn view of the standardization of clinical diagnosis and treatment of the acute abdomen and the inheritance of diagnosis and treatment experience of prestigious veteran traditional Chinese medicine（TCM） doctors， a diagnosis and treatment reasoning algorithm based on association rule mining under incomplete evidence（AMIE）+ random walk was proposed to provide information services and technical support for primary doctors by recommending personalized diagnosis and treatment plans based on medical records. MethodThe experience of diagnosis and treatment of acute abdomen of prestigious veteran TCM doctors and the text data of clinical diagnosis and treatment guidelines of integrated TCM and western medicine were collected to complete the task of knowledge extraction and construct acute abdomen knowledge graph based on Neo4j. On the basis of ontology-supported rule-based reasoning， the rule reasoning based on similar syndromes was used to expand the syndrome combinations whose Jaccard similarity was greater than the threshold in the syndrome recommendation results. The semantic path coverage algorithm was used to calculate the semantic similarity between the symptom nodes. The symptom nodes were divided into 10 categories， and the symptom nodes in the same category were extended. The random walk algorithm was used to search the symptom nodes connected with the syndrome， and the connection rules between the syndrome and symptom nodes were extended to realize the knowledge reasoning of AMIE+ random walk. ResultThe acute abdomen knowledge graph included 1 320 nodes and 2 464 relationships. According to the link prediction evaluation index of knowledge reasoning， the reasoning results of the three algorithms in the auxiliary diagnosis and treatment of acute abdomen were compared. The AMIE+ random walk algorithm complemented the knowledge graph by extending the similar syndrome connection rules and the syndrome-symptom connection rules. Compared with the knowledge reasoning algorithm based on ontology rules， the area under the curve （AUC） was 15.18% higher and the accuracy was 30.36% higher， which achieved more accurate and effective knowledge inference. ConclusionThis study used knowledge graph technology to visualize the diagnosis and treatment of acute abdomen with TCM and western medicine， assisting primary clinicians in intuitively viewing the diagnosis and treatment process and data relationship. The proposed diagnosis and treatment reasoning algorithm can realize the personalized diagnosis and treatment plan recommendation at the level of "disease-syndrome-diagnosis-treatment-prescription"， which can assist primary doctors in disease diagnosis and treatment and clinical decision-making， contribute to the knowledge sharing and application of diagnosis and treatment experience and clinical guidelines of prestigious veteran TCM doctors， improve the level of primary clinical diagnosis and treatment， and promote the normalization and standardization of the diagnosis and treatment process of acute abdomen with integrated TCM and western medicine.

Knowledge Graph Construction of Coronary Heart Disease Based on Traditional Chinese Medicine Diagnosis and Treatment Guidelines / 中国实验方剂学杂志

ObjectiveTo construct the syndrome differentiation and treatment process in the diagnosis and treatment guideline into a visual knowledge graph using knowledge graph technology， and visualize the process from the input of clinical manifestations to the output of corresponding traditional Chinese medicine （TCM） diagnosis and prescriptions through programs， to visually display the diagnosis and treatment process as well as the data relationship for TCM practitioners. This paper facilitated the standardized and normalized TCM diagnosis and treatment of coronary heart disease， and provided technical support for the inheritance and promotion of TCM diagnosis and treatment. MethodNeo4j and py2neo were used to construct a knowledge graph based on the Guideline for Diagnosis and Treatment of Coronary Heart Disease with Stable Angina Pectoris published by China Association of Chinese Medicine Cardiovascular Disease Branch. A knowledge graph regarding the input of clinical manifestations was built through programs， visually displaying the standardized TCM diagnosis and treatment process of coronary heart disease with stable angina pectoris. ResultThe structured data were extracted from the guideline by py2neo connecting to Neo4j and imported into Neo4j to construct the knowledge graph of TCM diagnosis and treatment of coronary heart disease with stable angina pectoris， which had graph database query function. ConclusionAiming at the problems existing in the inheritance of TCM diagnosis and treatment， this paper proposed a diagnosis and treatment guideline integrating the experience of TCM experts and evidence-based evidence for coronary heart disease with stable angina pectoris， and realized the visualization process of knowledge graph based on TCM diagnosis and treatment guideline and the experience of TCM experts. It is helpful to intuitively display the whole TCM diagnosis and treatment process from symptom input to prescriptions and inherit TCM experience， providing a new paradigm for standardized and normalized TCM diagnosis and treatment.

Drug repurposing for Alzheimer''s disease using knowledge graph embedding / 中国药科大学学报

@#Alzheimer''s disease (AD) has brought to us huge medical and economic burdens, and so discovery of its therapeutic drugs is of great significance.In this paper, we utilized knowledge graph embedding (KGE) models to explore drug repurposing for AD on the publicly available drug repurposing knowledge graph (DRKG).Specifically, we applied four KGE models, namely TransE, DistMult, ComplEx, and RotatE, to learn the embedding vectors of entities and relations on DRKG.By using three classical knowledge graph evaluation metrics, we then evaluated and compared the performance of these models as well as the quality of the learned embedded vectors.Based on our results, we selected the RotatE model for link prediction and identified 16 drugs that might be repurposed for the treatment of AD.Previous studies have confirmed the potential therapeutic effects of 12 drugs against AD, i.e., glutathione, haloperidol, capsaicin, quercetin, estradiol, glucose, disulfire, adenosine, paroxetine, paclitaxel, glybride and amitriptyline.Our study demonstrates that drug repurposing based on KGE may provide new ideas and methods for AD drug discovery.Moreover, the RotatE model effectively integrates multi-source information of DRKG, enabling promising AD drug repurposing.The source code of this paper is available at https://github.com/LuYF-Lemon-love/AD-KGE.

Entity extraction and graph construction based on Chinese medical text / 中国药科大学学报

@#Knowledge graph technology has promoted the progress of new drug research and development, but domestic research starts late and domain knowledge is mostly stored in text, resulting in low rate of knowledge graph reuse.Based on multi-source and heterogeneous medical texts, this paper designed a Chinese named entity recognition model based on Bert-wwm-ext pre-training model and also integrated cascade thought, which reduced the complexity of traditional single classification and further improved the efficiency of text recognition.The experimental results showed that the model achieved the best performance with an F1-score of 0.903, a precision of 89.2%, and a recall rate of 91.5% on the self-built dataset.At the same time, the model was applied to the public dataset CCKS2019, and the results showed that the model had better performance and recognition effect.Using this model, this paper constructed a Chinese medical knowledge graph, involving 13 530 entities, 10 939 attributes and 39 247 relationships of them in total.The Chinese medical entity extraction and graph construction method proposed in this paper is expected to help researchers accelerate the new discovery of medical knowledge, and shorten the process of new drug discovery.

Knowledge graph analysis of pyroptosis research in traditional Chinese medicine based on VOSviewer and CiteSpace / 中国中药杂志

To explore the research hotspots and frontier directions of pyroptosis in the field of traditional Chinese medicine(TCM), the authors searched CNKI and Web of Science for literature related to pyroptosis in TCM, screened literature according to the search strategy and inclusion criteria, and analyzed the publication trend of the included literature. VOSviewer was used to draw author cooperation and keyword co-occurrence network diagrams, and CiteSpace was employed for keyword clustering, emergence, and timeline view. Finally, 507 Chinese literature and 464 English literature were included, and it was found that the number of Chinese and English literature was increasing rapidly year by year. The co-occurrence of the authors showed that in terms of Chinese literature, there was a representative research team composed of DU Guan-hua, WANG Shou-bao and FANG Lian-hua, and for English literature, the representative research team was composed of XIAO Xiao-he, BAI Zhao-fang and XU Guang. The network visualization of Chinese and English keywords revealed that inflammation, apoptosis, oxidative stress, autophagy, organ damage, fibrosis, atherosclerosis, and ischemia-reperfusion injury were the primary research diseases and pathological processes in TCM; berberine, resveratrol, puerarin, na-ringenin, astragaloside Ⅳ, and baicalin were the representative active ingredients; NLRP3/caspase-1/GSDMD, TLR4/NF-κB/NLRP3, and p38/MAPK signaling pathways were the main research pathways. Keyword clustering, emergence, and timeline analysis indicated that the pyroptosis research in TCM focused on the mechanism of TCM monomers and compounds intervening in diseases and pathological processes. Pyroptosis is a research hotspot in the area of TCM, and the current discussion mainly focuses on the mechanism of the therapeutic effect of TCM.

Study on the explicitation of implicit knowledge and the construction of knowledge graph on moxibustion in medical case records of ZHOU Mei-sheng's Jiusheng / 中国针灸

To explore the methods of the explicitation of implicit knowledge and the construction of knowledge graph on moxibustion in medical case records of ZHOU Mei-sheng's Jiusheng. The medical case records data of Jiusheng was collected, the frequency statistic was analyzed based on Python3.8.6, complex network analysis was performed using Gephi9.2 software, community analysis was performed by the ancient and modern medical case cloud platform V2.3.5, and analysis and verification of correlation graph and weight graph were proceed by Neo4j3.5.25 image database. The disease systems with frequency≥10 % were surgery, ophthalmology and otorhinolaryngology, locomotor, digestive and respiratory systems. The diseases under the disease system were mainly carbuncle, arthritis, lumbar disc herniation and headache. The commonly used moxibustion methods were fumigating moxibustion, blowing moxibustion, direct moxibustion and warming acupuncture. The core prescription of points obtained by complex network analysis included Yatong point, Zhiyang(GV 9), Sanyinjiao(SP 6), Dazhui(GV 14), Zusanli(ST 36), Lingtai(GV 10), Xinshu(BL 15), Zhijian point and Hegu(LI 4), which were basically consistent with high-frequency points. A total of 6 communities were obtained by community analysis, corresponding to different diseases. Through the analysis of correlation graph, 13 pairs of strong association rule points were obtained. The correlation between Zhiyang(GV 9)-Dazhui(GV 14) and Yatong point-Lingtai(GV 10) was the strongest. The acupoints with high correlation with Yatong point were Zhiyang(GV 9), Lingtai(GV 10), Dazhui(GV 14), Zusanli(ST 36) and Sanyinjiao(SP 6). In the weight graph of the high-frequency disease system, the relationship of the first weight of the surgery system disease was fumigating moxibustion-carbuncle-Yatong point, and the relationship of the first weight of the ophthalmology and otorhinolaryngology system disease was blowing moxibustion-laryngitis-Hegu (LI 4). The results of correlation graph and weight graph are consistent with the results of data mining, which can be used as an effective way to study the knowledge base of moxibustion diagnosis and treatment in the future.

Design and Implementation of Intelligent Question Answering System of Marine Traditional Chinese Medicine Based on Knowledge Graph / 世界科学技术-中医药现代化

Objective In order to solve the problem of insufficient public understanding of the information of Marine Traditional Chinese Medicine and the lack of relevant knowledge service tools of Marine Traditional Chinese Medicine,the research and development of an intelligent question-answering system for Marine Traditional Chinese Medicine have been carried out,to provide a tool for public to inquire the knowledge of Marine Traditional Chinese Medicine.Methods The knowledge base is based on the fine-sized Marine Traditional Chinese Medicine knowledge graph MMKG constructed in the early stage.Aho-Corasick,Word2Vec and other algorithms were used to obtain Marine Traditional Chinese Medicine entities.From the professional point of view,a fine-sized classification method for Marine Traditional Chinese Medicine questions was proposed,and an intelligent Marine Traditional Chinese Medicine question answering system(MMKGQA)was constructed.Results The average accuracy rate,average recall rate and average F1 value of the system were 97.93%,83.41%and 89.10%,respectively,through the question corpus test of the questionnaire survey.It shows that the system can answer the relevant questions of Marine Traditional Chinese Medicine well and has high practicability and feasibility.Conclusion This system can help common users to obtain the popular science knowledge of Marine Traditional Chinese Medicine and provide an effective knowledge service tool for the researchers of Marine Traditional Chinese Medicine to acquire relevant knowledge and help the research and development of Marine new drugs.

Research on the Construction Method and Application of Diagnosis and Treatment Knowledge Graph of Famous TCM Physicians Based on Medical Records / 世界科学技术-中医药现代化

Objective A knowledge graph construction pipeline of traditional Chinese medicine(TCM)diagnosis and treatment was designed and applied,aiming at the automatic construction of the"disease-symptom-pathogenesis-and medicine"knowledge graph based on the medical records of famous TCM physicians,to analyze,organize and present medical records efficiently.Methods Firstly,The entity extraction method of medical records combining Deep Learning and Regular Expression was designed to extract disease,symptom,pathogenesis,and TCM entities from unstructured medical records automatically;secondly,entity relationships were defined and the correlations between entities were calculated using HAN method,and then the"entity-relation-entity"triplets were built;the graph database Neo4j and Gephi were used for knowledge storage and visual display separately;Finally,the application was verified in the Medical records of lung cancer treated by the old famous TCM physicians.Results The precision,Recall and F1 of the knowledge extraction model for medical records entities extraction are 88.49%,90.02%and 89.25%,respectively,and each index is better than the comparison methods.A total of 1077 triples are extracted through entity correlation calculation,and the knowledge graph is successfully constructed.It can reflect the relationship between 'disease-symptom-pathogenesis-medicine' in the treatment of lung cancer by the famous specialists of TCM.Conclusion The method in this paper can effectively solve the extraction,organization and expression of clinical medical records of famous TCM physicians,and realize the automatic construction process from the text of medical records to the knowledge graph.Relevant research ideas and methods proposed in this paper could provide a reference for the construction of the diagnosis and treatment knowledge graph of famous TCM physicians based on medical records.