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text mining of Rheumatoid Arthritis and Diabetes Mellitus to Understand the Mechanisms of Chinese Medicine in Different Diseases with Same Treatment

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Chinese Journal of Integrative Medicine 2018年第10期24卷 777-784页

作者： ZHAO Ning ZHENG Guang LI Jian ZHAO Hong-yan LU Cheng JIANG Miao ZHANG Chi GUO Hong-tao LU Ai-ping Institute of Basic Research in Clinical Medicine China Academy of Chinese Medical Sciences School of Information Science and Engineering Lanzhou University School of Basic Medical Sciences Beijing University of Chinese Medicine Institute of Basic Theory for Chinese Medicine China Academy of Chinese Medical Sciences School of Chinese Medicine Hong Kong Baptist University

Objective： To identify the commonalities between rheumatoid arthritis （RA） and diabetes mellitus （DM） to understand the mechanisms of Chinese medicine （CM） in different diseases with the same treatment. Methods： A text mining approach was adopted to analyze the commonalities between RA and DM according to CM and biological elements. The major commonalities were subsequently verified in RA and DM rat models, in which herbal formula for the treatment of both RA and DM identified via text mining was used as the intervention. Results： Similarities were identified between RA and DM regarding the CM approach used for diagnosis and treatment, as well as the networks of biological activities affected by each disease, including the involvement of adhesion molecules, oxidative stress, cytokines, T-lymphocytes, apoptosis, and inflammation. The Ramulus Cinnamomi-Radix Paeoniae Alba-Rhizoma Anemarrhenae is an herbal combination used to treat RA and DM. This formula demonstrated similar effects on oxidative stress and inflammation in rats with collagen-induced arthritis, which supports the text mining results regarding the commonalities between RA and DM. Conclusion： Commonalities between the biological activities involved in RA and DM were identified through text mining, and both RA and DM might be responsive to the same intervention at a specific stage.

关键词： text mining rheumatoid arthritis diabetes mellitus different diseases with same treatment Chinese medicine

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Assessing trends in wildland-urban interface fire research through text mining: a comprehensive analysis of published literature

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Journal of Forestry Research 2024年第4期35卷 102-114页

作者： Hafsae Lamsaf Asmae Lamsaf Mounir A.Kerroum Miguel Almeida ADAI–Associação para o Desenvolvimento da Aerodinâmica Industrial Rua Pedro Hispano n.º123030‑289 CoimbraPortugal Laboratory of Research in Computer Science Faculty of SciencesIbn Tofail UniversityKenitraMorocco

Research on fires at the wildland-urban inter-face(WUI)has generated significant insights and advance-ments across various fields of ***,agri-culture,and social sciences have played prominent roles in understanding the impacts of fires in the environment,in protecting communities,and addressing management *** study aimed to create a database using a text mining technique for global researchers interested in WUI-projects and highlighting the interest of countries in this ***’s-Keywords analysis emphasized the dominance of fire science-related terms,especially related to WUI,and identified keyword clusters related to the WUI fire-risk-assessment-system-“exposure”,“danger”,and“vulnerability”within wildfire *** over the past decade showcase shifting research interests with a growing focus on WUI fires,while regional variations highlighted that the“exposure”keyword cluster received greater atten-tion in the southern Europe and South ***,vulnerability keywords have relatively a lower representation across all *** analysis underscores the interdisci-plinary nature of WUI research and emphasizes the need for targeted approaches to address the unique challenges of the wildland-urban ***,this study provides valu-able insights for researchers and serves as a foundation for further collaboration in this field through the understanding of the trends over recent years and in different regions.

关键词： WUI text mining Wildfires Fire science State of the art Scientific publications

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Deep Analysis of Power Equipment Defects Based on Semantic Framework text mining Technology

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1157-1164页

作者： Huifang Wang Jing Cao Dongyang Lin Electrical Engineering Department Zhejiang UniversityHangzhou 310058China State Grid Jiangsu Electric Power Engineering Consulting Co. Ltd.Nanjing 210000China

Defect factors and their relevant rules can be analyzed in depth by processing defect records which are often expressed in the form of text ***,considering that defect text consists of both structured and unstructured data,it is necessary to excavate structured information from unstructured *** this paper,a text mining method based on semantic framework technology is introduced to transform unstructured defect description into structured information such as components and defect ***,a deep analyzing model of a power equipment defect is established,which provides a scheme of defect mining based on historical defect *** studies prove that the proposed deep analysis method has a guiding significance for equipment upgrading,selection and maintenance.

关键词： Age curve defect analysis defect rate factor study power equipment text mining

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text mining and Analysis of Treatise on Febrile Diseases Based on Natural Language Processing

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World Journal of Traditional Chinese Medicine 2020年第1期6卷 67-73页

作者： Kai Zhao Na Shi Zhen Sa Hua-Xing Wang Chun-Hua Lu Xiao-Ying Xu School of Traditional Chinese Medicine Beijing University of Chinese Medicine School of Life Science Beijing University of Chinese Medicine Beijing 100029China

Objective:With using natural language processing (NLP) technology to analyze and process the text of "Treatise on Febrile Diseases (TFDs)"for the sake of finding important information, this paper attempts to apply NLP in the field of text mining of traditional Chinese medicine (TCM)literature. Materials and Methods:Based on the Python language, the experiment invoked the NLP toolkit such as Jieba, nltk, gensim,and sklearn library, and combined with Excel and Word software. The text of "TFDs" was sequentially cleaned, segmented, and moved the stopped words, and then implementing word frequency statistics and analysis, keyword extraction, named entity recognition (NER) and other operations, finally calculating text similarity. Results:Jieba can accurately identify the herbal name in "TFDs." Word frequency statistics based on the word segmentation found that "warm therapy" is an important treatment of "TFDs." Guizhi decoction is the main prescription,and five core decoctions are identified. Keyword extraction based on the term "frequency-inverse document frequency" algorithm is *** accuracy of NER in "TFDs" is about 86%;latent semantic indexing model calculating the similarity,"Understanding of Synopsis of Golden Chamber (SGC)" is much more similar with "SGC" than with "TFDs." The results meet expectation. Conclusions:It lays a research foundation for applying NLP to the field of text mining of unstructured TCM literature. With the combination of deep learning technology,NLP as an important branch of artificial intelligence will have broader application prospective in the field of text mining in TCM literature and construction of TCM knowledge graph as well as TCM knowledge services.

关键词： Knowledge discovery natural language processing text mining traditional Chinese medicine literature treatise on febrile diseases

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Automatic Surveillance of Pandemics Using Big Data and text mining

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Computers, Materials & Continua 2021年第7期68卷 303-317页

作者： Abdullah Alharbi Wael Alosaimi MIrfan Uddin Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan

COVID-19 disease is spreading exponentially due to the rapid transmission of the virus between *** countries have tried different solutions to control the spread of the disease,including lockdowns of countries or cities,quarantines,isolation,sanitization,and *** with symptoms of COVID-19 are tested using medical testing kits;these tests must be conducted by healthcare ***,the testing process is expensive and *** is no surveillance system that can be used as surveillance framework to identify regions of infected individuals and determine the rate of spread so that precautions can be *** paper introduces a novel technique based on deep learning(DL)that can be used as a surveillance system to identify infected individuals by analyzing tweets related to *** system is used only for surveillance purposes to identify regions where the spread of COVID-19 is high;clinical tests should then be used to test and identify infected *** system proposed here uses recurrent neural networks(RNN)and word-embedding techniques to analyze tweets and determine whether a tweet provides information about COVID-19 or refers to individuals who have been infected with the *** results demonstrate that RNN can conduct this analysis more accurately than other machine learning(ML)algorithms.

关键词： Disease surveillance social media analysis recurrent neural networks text mining

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Blockchain technology forecasting by patent analytics and text mining

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Blockchain(Research and Applications) 2021年第2期2卷 97-110页

作者： Seyed Mojtaba Hosseini Bamakan Alireza Babaei Bondarti Parinaz Babaei Bondarti Qiang Qu Department of Industrial Management Yazd UniversityYazd89195-741Iran Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen518055China Department of Library and Information Science Kharazmi UniversityTehran15719-14911Iran

Information technologies(ITs)have been playing an important role in improving our society,and the fast evolution of ITs creates a competitive environment not only for companies but also for ***,recognizing the future trend of technologies can be effective in decision-making with regard to technology selection and *** technology with its vast and impressive applications has received considerable attention from researchers,investors,and public *** purpose of this research is to investigate blockchain technology to explore its trends according to their classification by use of the World Intellectual Property Organization(WIPO)***,we particularly evaluate the registered patents in the world's most well-known patent databases such as the USA patent *** drew the current technology trends in blockchain patents by applying the text mining and clustering *** results represent that the registered patents in the USA patent database have been achieved in the growth *** means,attention to the blockchain is rising nowadays and most patents focused the cryptocurrencies and their applications in ***,blockchain technology is in the emergence phase and is evolving by researchers and inventors.

关键词： Technology forecasting Blockchain technology Patent analysis text mining Technology life cycle

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The Early Emotional Responses and Central Issues of People in the Epicenter of the COVID-19 Pandemic: An Analysis from Twitter text mining

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International Journal of Mental Health Promotion 2023年第1期25卷 21-29页

作者： Eun-Joo Choi Yun-Jung Choi Department of Nursing Kyungin Women’s UniversityIncheon21041South Korea Red Cross College of Nursing Chung-Ang UniversitySeoul06974South Korea

This study aimed to explore citizens’emotional responses and issues of interest in the context of the coronavirus disease 2019(COVID-19)*** dataset comprised 65,313 tweets with the location marked as New York *** data collection period was four days of tweets when New York City imposed a lockdown order due to an increase in conﬁrmed *** analysis was performed using R *** emotional responses in tweets were analyzed using the Bing and NRC(National Research Council Canada)*** tweets’central issue was identiﬁed by text Network *** tweets were classiﬁed as either positive or negative,the negative sentiment was *** the NRC dictionary,eight emotional classiﬁcations were devised:“trust,”“fear,”“anticipation,”“sadness,”“anger,”“joy,”“surprise,”and“disgust.”These results indicated that citizens showed negative and trusting emotional reactions in the early days of the ***,citizens showed a strong interest in overcoming and coping with other people such as social *** were concerned about the conﬁrmation of COVID-19 infection status and *** should be made to ensure citizens’psychological stability by promptly informing them of the status of infectious disease management and the route of infection.

关键词： COVID-19 community mental health emotional responses text mining Twitter

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text mining and data analysis identify potential drugs and pathways for polycystic ovary syndrome treatment

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Reproductive and Developmental Medicine 2024年第1期8卷 32-38页

作者： Xiao-Jing Yuan Yan Wang Hai-Yan Yang Bin Zhao Medical Reproductive Center People's Hospital of Jiuquan CityJiuquan 735000China Department of Gynecological Oncology The Fourth Affiliated Hospital of Guangxi Medical UniversityLiuzhou 545000China Xiamen Health and Medical Big Data Center Xiamen361001China

Objective:Polycystic ovarian syndrome(PCOS)is a common endocrine disorder affecting women of reproductive *** study aimed to use text mining and microarray data analysis to identify drugs that target genes and potential pathways associated with ***:We extracted a common set of genes associated with PCOS using text mining and the microarray dataset ***,we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of these genes,as well as protein–protein interaction(PPI)network ***,we used MCODE and cytoHubba to cluster significant common genes in the PPI network and performed gene–drug interaction analyses to identify potential drugs for further ***,we annotated pathways associated with the genes ***:text mining and microarray analysis yielded 696 text mining genes(TMGs)and 2804 differentially expressed genes(DEGs).Among these,a set of 77 genes was found in both TMGs and ***,67 of these genes participated in constructing the PPI *** common hub genes were selected using the MCODE and CytoHubba ***,five out of seven genes were targeted by 15 existing ***:Four genes(FASLG,IL13,IL17A,andIL2RA),which are mainly related to the cytokine–cytokine receptor interaction pathway,could be prioritized as targets for PCOS.

关键词： text mining Differentially expressed genes Polycystic ovary syndrome Drug discovery

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Dynamic evaluation of digital and green development policies based on text mining of the PMC framework

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Journal of Southeast University(English Edition) 2024年第3期40卷 319-326页

作者： Ye Chunmei Wu Lihua School of Economics and Management Southeast UniversityNanjing 211189China

Aiming to identify policy topics and their evolutionary logic that enhance the digital and green development(dual development)of traditional manufacturing enterprises,address weaknesses in current policies,and provide resources for refining dual development policies,a total of 15954 dual development-related policies issued by national and various departmental authorities in China from January 2000 to August 2023 were *** on topic modeling techniques and the policy modeling consistency(PMC)framework,the evolution of policy topics was visualized,and a dynamic assessment of the policies was *** results show that the digital and green development policy framework is progressively refined,and the governance philosophy shifts from a“regulatory government”paradigm to a“service-oriented government”.The support pattern evolves from“dispersed matching”to“integrated symbiosis”.However,there are still significant deficiencies in departmental cooperation,balanced measures,coordinated links,and multi-stakeholder *** policy improvements should,therefore,focus on guiding multi-stakeholder participation,enhancing public demand orientation,and addressing the entire value *** steps aim to create an open and shared digital industry ecosystem to promote the coordinated dual development of traditional manufacturing enterprises.

关键词： digital and green development text mining topic modeling policy modeling consistency(PMC)framework machine learning

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Uncovering the influence of ChatGPT's prompts on traffic safety information using text mining approach

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Data Science and Informetrics 2023年第4期3卷 1-21页

作者： Boniphace Kutela Kelvin J.Msechu Norris Novat Emmanuel Kidando Angela E.Kitali Texas A&M Transportation Institute HoustonUSA Atkins North America Inc. NoviUSA IterisInc. FairfaxUSA Department of Civil and Environmental Engineering Cleveland State UniversityClevelandUSA School of Engineering and Technology University of Washington TacomaTacomaUSA

ChatGPT has emerged as a promising advanced large language model that needs prompt to gain ***,designing a good prompt is not an easy task for many ***,this study intends to determine the amount of information gained because of varied amounts of information in the *** study used two types of prompts,initial and improved,to query the introduction sections of 327 highly cited articles on traffic *** queried introduction sections were then matched with the corresponding human-written introduction sections from the same *** tests and text network analysis were used to understand the level of similarities and the content of ChatGPT-generated and human-written *** findings indicate the improved prompts,which have the addition of generic persona and information about the citations and references,changed the ChatGPT's output *** the perfect similar contents are supposed to have a 1.0 similarity score,the initial and improved prompt's introduction materials have average similarity scores of 0.5387 and 0.5567,***,the content analysis revealed that themes such as statistics,trends,safety measures,and safety technologies are more likely to have high similarity scores,irrespective of the amount of information provided in the *** the other hand,themes such as human behavior,policy and regulations,public perception,and emerging technologies require a detailed level of information in their prompt to produce materials that are close to human-written *** prompt engineers can use the findings to evaluate their outputs and improve their prompting skills.

关键词： ChatGPT Artificial intelligence Prompt Traffic safety text mining

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