CorText Manager around the world

@article{Shen2025,

title = {From virtual to reality: innovative practices of digital twins in tumor therapy},

author = {Shiying Shen and Wenhao and Xin Liu and Jianwen Zeng and Sixie Li and Xiaohong Zhu and Chaoqun Dong and Bin Wang and Yankai Shi and Jiani Yao and Bingsheng Wang and Louxia Jing and Shihua Cao and Guanmian Liang},

url = {https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-025-06371-z},

doi = {/10.1186/s12967-025-06371-z},

year  = {2025},

date = {2025-03-19},

urldate = {2025-03-19},

journal = {Journal of Translational Medicine},

volume = {23},

issue = {348},

abstract = {Background As global cancer incidence and mortality rise, digital twin technology in precision medicine offers new opportunities for cancer treatment.

Objective This study aims to systematically analyze the current applications, research trends, and challenges of digital twin technology in tumor therapy, while exploring future directions.

Methods Relevant literature up to 2024 was retrieved from PubMed, Web of Science, and other databases. Data visualization was performed using R and VOSviewer software. The analysis includes the research initiation and trends, funding models, global research distribution, sample size analysis, and data processing and artificial intelligence applications. Furthermore, the study investigates the specific applications and effectiveness of digital twin technology in tumor diagnosis, treatment decision-making, prognosis prediction, and personalized management.

Results Since 2020, research on digital twin technology in oncology has surged, with significant contributions from the United States, Germany, Switzerland, and China. Funding primarily comes from government agencies, particularly the National Institutes of Health in the U.S. Sample size analysis reveals that large-sample studies have greater clinical reliability, while small-sample studies emphasize technology validation. In data processing and artificial intelligence applications, the integration of medical imaging, multi-omics data, and AI algorithms is key. By combining multimodal data integration with dynamic modeling, the accuracy of digital twin models has been significantly improved.

However, the integration of different data types still faces challenges related to tool interoperability and limited standardization. Specific applications of digital twin technology have shown significant advantages in diagnosis, treatment

decision-making, prognosis prediction, and surgical planning.

Conclusion Digital twin technology holds substantial promise in tumor therapy by optimizing personalized treatment plans through integrated multimodal data and dynamic modeling. However, the study is limited by factors such as language restrictions, potential selection bias, and the relatively small number of published studies in this emerging field, which may affect the comprehensiveness and generalizability of our findings. Moreover, issues related to data heterogeneity, technical integration, and data privacy and ethics continue to impede its broader clinical application. Future research should promote international collaboration, establish unified interdisciplinary standards, and strengthen ethical regulations to accelerate the clinical translation of digital twin technology in cancer treatment.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Nemati-Anaraki2024,

title = {A bibliometric Overview and visualization of Koomesh Journal from 2006 to 2022},

author = {Leila Nemati-Anaraki and Ali Ouchi and Maedeh Pourmojdegani},

url = {https://repository.brieflands.com/handle/123456789/61490

https://repository.brieflands.com/items/9d70b205-f684-489b-a781-1dc6b40049fb

https://brieflands.com/articles/koomesh-152853.pdf},

year  = {2024},

date = {2024-08-06},

urldate = {2024-08-06},

journal = {Koomesh},

volume = {25},

issue = {4},

pages = {535-549},

publisher = {Brieflands},

address = {Iran},

abstract = {هدف:مجله کومشيکمجله قديميو پيشرودر ايراناست که از سال2006به عنوان بستريبرايتحقيقاتحوزه پزشکي

خدمت کرده است. هدف اصلياينمطالعه ارائهيکنمايکلياز ساختار انتشارات مجله کومش طيسالهاي2006تا2022از

طريقتحليلکتابسنجياست.

مواد و روشها:اينمطالعه با رويکردکتابسنجيانجام شد. جامعه مطالعه را1238سند منتشر شده در مجله کومش

تشکيلميدهد.دادههايکتابشناختيايناسناد از پايگاهداده اسکوپوس استخراج شد و روندها و موضوعات مهم مجله مانند

ساختار انتشار و استناد مجله، مقاالت پر استناد آن، نويسندگان،مؤسسات و کشورها با استفاده از طيفوسيعيازتکنيکها و

ابزارهايمختلف کتابسنجياز جمله اکسل،SPSSنسخه26،VOS Viewer،CorTexوBiblioshinyاستخراج شد.

يافتهها:کومش هم از نظر بهرهوريو هم از نظر نفوذ ابتدا با افت و خيزهاييرشد کرده و سپس کاهشيافتهاست. دانشگاه

علوم پزشکيسمنان و کشور ايرانبه ترتيبموسسه و کشور با بيشتريندرصد مشارکت در اينمجله هستند. راهب قرباني

تاثيرگذارترينو پرکارتريننويسندهکومش بود. ميزان همتاليفي ًنسبتاخوبيبيننويسندگانبرتر مجله وجود دارد. بيشترين

همتاليفيبينکشورهايايرانو سوئد و از نظر شهر، بينتهران و سمنان صورت گرفته است. کلمات ايران،ورزش و اضطراببه

ترتيبسه کلمه مهم و پرتکرار نويسندگانبوده است. بيشترينبحث نيزبر رويموضوعاتprecision medicineو کوويد-19

بود.

نتيجهگيري:اينمطالعهيکنمايکلياز ساختار انتشارات مجله کومش طيسالهاي2006تا2022ارائه کرده است. اين

مطالعه ممکن است برايهيئتتحريريهمجله مفيدباشد، زيرااطالعات متعدد و مفيديرا برايپيشرفتو ادامه راهکومش

فراهم ميکند.



Introduction: The Koomesh Journal, a pioneering and influential medical research publication in Iran, has been active since 2006. This study aims to offer a comprehensive overview of the journal's publication structure from 2006 to 2022 using bibliometric analysis.

Materials and Methods: This study was conducted with a bibliometric approach. The study population consists of 1238 documents published in the Koomesh Journal. The bibliographic data of these documents were extracted from the Scopus database, and various bibliometric techniques and tools, such as Excel 365, SPSS 26, VOS Viewer, CorTex, and Biblioshiny, were extracted to examine trends and significant topics such as the journal's publication and citation structure, highly cited articles, authors, institutions, and countries.

Results: Koomesh experienced fluctuations in productivity and impact before declining. Semnan University of Medical Sciences and Iran were the institutions and countries with the highest participation rates, respectively. Raheb Ghorbani emerged as the most influential and prolific author. The article "Estimation of natural age of menopause in Iranian women: A meta-analysis study" received the most citations. A considerable degree of co-authorship existed among the journal's top authors, with the most collaboration occurring between Iran and Sweden and, in terms of cities, Tehran and Semnan. The terms Iran, sports, and anxiety were the most prevalent and significant. The most discussion was on precision medicine and COVID-19.

Conclusion: This study has provided an overview of the publication structure of Koomesh Journal during the years 2006 to 2022. This study may be useful for the editorial board of the journal, because it provides numerous and useful information for the progress and continuation of the work.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Skovgaard2023,

title = {Who tweets what about personalised medicine? Promises and concerns from Twitter discussions in Denmark},

author = {Lea Skovgaard and Anders Grundtvig},

url = {https://journals.sagepub.com/doi/pdf/10.1177/20552076231169832},

doi = {10.1177/20552076231169832},

year  = {2023},

date = {2023-03-29},

urldate = {2023-03-29},

journal = {Digital Health},

volume = {9},

pages = {1-12},

abstract = {Digital health data are seen as valuable resources for the development of better and more efficient treatments, for instance through personalised medicine. However, health data are information about individuals who hold opinions and can challenge how data about them are used. Therefore it is important to understand public discussions around reuse of digital health data. Social media have been heralded as enabling new forms of public engagement and as a place to study social issues. In this paper, we study a public debate on Twitter about personalised medicine. We explore who participates in discussions about personalised medicine on Twitter and what they tweet about. Based on user-generated biographies we categorise users as having a ‘Professional interest in personalised medicine’ or as ‘Private’ users. We describe how users within the field tweet about the promises of personalised medicine, while users unaffiliated with the field tweet about the concrete realisation of these ambitions in the form of a new infrastructure and express concerns about the conditions for the implementation. Our study serves to remind people interested in public opinion that Twitter is a platform used for multiple purposes by different actors and not simply a bottom-up democratic forum. This study contributes with insights relevant to policymakers wishing to expand infrastructures for reuse of health data. First, by providing insights into what is discussed about health data reuse. Second, by exploring how Twitter can be used as a platform to study public discussions about reuse

of health data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Duan2023,

title = {The research hotspots and trends of volatile organic compound emissions from anthropogenic and natural sources: A systematic quantitative review},

author = {Chensong Duan and Hu Liao and Kaide Wang and Yin Ren},

url = {https://www.sciencedirect.com/science/article/pii/S0013935122017133?via%3Dihub



},

doi = {https://doi.org/10.1016/j.envres.2022.114386},

year  = {2023},

date = {2023-02-01},

urldate = {2023-02-01},

journal = {Environmental Research},

volume = {216},

pages = {114964},

abstract = {Volatile organic compound (VOC) emissions have attracted wide attention due to their impacts on atmospheric quality and public health. However, most studies reviewed certain aspects of natural VOCs (NVOCs) or anthropogenic VOCs (AVOCs) rather than comprehensively quantifying the hotspots and evolution trends of AVOCs and NVOCs. We combined the bibliometric method with the evolution tree and Markov chain to identify research focus and uncover the trends in VOC emission sources. This study found that research mainly focused on VOC emission characteristics, effects on air quality and health, and VOC emissions under climate change. More studies concerned on AVOCs than on NVOCs, and AVOC emissions have shifted with a decreasing proportion of transport emissions and an increasing share of solvent utilization in countries with high emissions and publications (China and the USA). Research on AVOCs is imperative to develop efficient and economical abatement techniques specific to solvent sources or BTEX species to mitigate the detrimental effects. Research on NVOCs originating from human sources risen due to their application in medicine, while studies on sources sensitive to climate change grew slowly, including plants, biomass burning, microbes, soil and oceans. Research on the long-term responses of NVOCs derived from various sources to climate warming is warranted to explore the evolution of emissions and the feedback on global climate. It is worthwhile to establish an emission inventory with all kinds of sources, accurate estimation, high spatial and temporal resolution to capture the emission trends in the synergy of industrialization and climate change as well as to simulate the effects on air quality. We review VOC emissions from both anthropogenic and natural sources under climate change and their effects on atmospheric quality and health to point out the research directions for the comprehensive control of global VOCs and mitigation of O3 pollution.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Louvel2022,

title = {Biological embedding vs. embodiment of social experiences: How these two concepts form distinct thought styles around the social production of health inequalities},

author = {Séverine Louvel and Alexandra Soulier},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0277953622007766?via%3Dihub},

doi = {https://doi.org/10.1016/j.socscimed.2022.115470},

year  = {2022},

date = {2022-10-01},

urldate = {2022-10-01},

journal = {Social Science & Medicine},

volume = {314},

issue = {115470},

abstract = {Objectives



This article compares research on biological embedding and the embodiment of social experiences, two concepts proposed in the 1990s to introduce a new perspective on the social production of health inequalities. We draw on Ludwig Fleck's concept of ‘thought style’ (1935/2008) to question the possible emergence of a common research program around the processes by which the social becomes biological.



Methods

We compiled a corpus of 322 articles referring to either biological embedding or to the embodiment of social experiences, identified in the Web of Science core collection and published from 1990 to 2021. We analyzed the articles’ use of these concepts using scientometric indicators and qualitative content analysis.



Results

Initial differences between the research agendas associated with biological embedding and embodiment are strengthened as both concepts circulate around scientific communities studying the social production of health inequalities. Thought styles formed around embedding and embodiment differ significantly in terms of shared references, sets of methods and research questions, and policy recommendations. Research on biological embedding forms a thought style shared by researchers in the biomedical and public health sciences. Conversely, the concept of embodiment of social experiences connects perspectives from biomedical, public health, human and social sciences, and gathers three thought styles, one identical to that of biological embedding and two formed in social epidemiology and in medical anthropology.



Conclusions

Acknowledging the differences between the concepts and divergences in their evolution provides an opportunity for identification of topics where thought styles are either complementary or in tension.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Carrillo2022,

title = {Academic dependency: the influence of the prevailing international biomedical research agenda on Argentina’s CONICET},

author = {Mercedes García Carrillo and Federico Testoni and Marc-André Gagnon and Cecilia Rikap and Matías Blaustein},

url = {https://linkinghub.elsevier.com/retrieve/pii/S2405844022027694

https://www.cell.com/action/showPdf?pii=S2405-8440%2822%2902769-4},

doi = {https://doi.org/10.1016/j.heliyon.2022.e11481},

year  = {2022},

date = {2022-09-01},

urldate = {2022-09-01},

journal = {Heliyon},

volume = {8},

abstract = {Background

The prevailing health and biomedical sciences (HBMS) research agenda, not only determined by leading academic institutions but also by large pharmaceutical companies, has been shown to prioritize the exploration of novel pharmacological interventions over the study of the socio-environmental factors influencing illness onset and progression. The aim of this investigation is to quantitatively explore whether and to what extent the prevailing international HBMS research agenda and the key actors setting this agenda influence research in non-core countries.

Methods

We used the Web of Science database and the CorText platform to proxy the HBMS research agenda of a prestigious research institution from Latin America: Argentina’s National Research Council (CONICET). We conducted a bibliometric and lexical analysis of 16,309 HBMS academic articles whereby CONICET was among the authors' affiliations. The content of CONICET’s agenda was represented through co-occurrence network maps of the most frequent concatenation of terms found in titles, keywords, and abstracts. We compared our findings with previous reports on the international HBMS research agenda.

Results

In line with the results previously reported for the prevailing international agenda, we found that terms linked to molecular biology and cancer research hegemonize CONICET’s HBMS research agenda, whereas terms connecting HBMS research with socio-environmental cues are marginal. However, we also found differences with the international agenda: CONICET's HBMS agenda shows a marginal presence of terms linked to translational medicine, while terms associated with categories such as pathogens, plant research, agrobiotechnology, and food industry are more represented than in the prevailing agenda.

Conclusions

CONICET’s HBMS research agenda shares topics, priorities, and methodologies with the prevailing HBMS international research agenda. However, CONICET's HBMS research agenda is internally heterogeneous, appearing to be mostly driven by a combination of elements that not only reflect academic dependency (the adoption of the prevailing research agenda by non-core research institutions) but also local economic determinants associated with Argentina’s place in the international division of labor as an exporter of primary goods.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Luo2022b,

title = {Food Supply Chain Safety Research Trends From 1997 to 2020: A Bibliometric Analysis},

author = {Jianli Luo and Shujuan Leng and Yanhu Bai},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850300/},

doi = {10.3389/fpubh.2021.742980},

year  = {2022},

date = {2022-02-03},

urldate = {2022-02-03},

journal = {National Library of Medicine},

volume = {9},

number = {742980},

abstract = {Background

The COVID-19 pandemic has exposed the fragility of the global food supply chain, strengthened consumers' awareness of the traceability system throughout the supply chain, and gradually changed consumers' consumption concepts and consumption patterns. Therefore, the aim of this study was to analyse the relevant literature on food safety in the food supply chain, examine its current status, hot spots, and development trends, and provide some suggestions for academics and relevant government departments in food supply chain safety research.



Methods

We collected the literature on the food safety research of the food supply chain from the Scopus database, used BibExcel to count the subject categories, published journals, geographical distributions, research institutions, authors, and keywords in the literature, and used Pajek software to analyse the keywords in the literature, perform co-occurrence analysis, draw related knowledge maps, and perform cluster analysis on primary keywords. Finally, to study the development trend, we used CorTexT software to illustrate the theme evolution path map in this research field.



Results

The keyword visualization network revealed the following key research topics: (1) food safety at the consumer end of the food supply chain, (2) food safety management in the food supply chain, (3) risk management of food safety in the food safety chain, and (4) food safety at the production end of the food supply chain.



Conclusions

After comprehensive discussion and analysis, we concluded that food supply chain management may be a hot topic in the future, especially in traceability management combined with the blockchain. It is necessary to explore in-depth how the blockchain can affect the food supply chain to provide a theoretical basis for managing the latter.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Zhao2021,

title = {Is coronavirus-related research becoming more interdisciplinary? A perspective of co-occurrence analysis and diversity measure of scientific articles},

author = {Yi Zhao and Lifan Liu and Chengzhi Zhang},

doi = {https://doi.org/10.1016/j.techfore.2021.121344},

year  = {2021},

date = {2021-11-08},

urldate = {2021-11-08},

journal = {Technological Forecasting and Social Change},

volume = {121344},

abstract = {The outbreak of coronavirus disease 2019 (COVID-19) has had a significant repercussion on the health, economy, politics and environment, making coronavirus-related issues more complicated and difficult to adequately address by relying on a single field. Interdisciplinary research can provide an effective solution to complex issues in the related field of coronavirus. However, whether coronavirus-related research becomes more interdisciplinary still needs corroboration. In this study, we investigate interdisciplinary status of the coronavirus-related fields via the COVID-19 Open Research Dataset (CORD-19). To this end, we calculate bibliometric indicators of interdisciplinarity and apply a co-occurrence analysis method. The results show that co-occurrence relationships between cited disciplines have evolved dynamically over time. The two types of co-occurrence relationships, Immunology and Microbiology & Medicine and Chemical Engineering & Chemistry, last for a long time in this field during 1990–2020. Moreover, the number of disciplines cited by coronavirus-related research increases, whereas the distribution of disciplines is uneven, and this field tends to focus on several dominant disciplines such as Medicine, Immunology and Microbiology, Biochemistry, Genetics and Molecular Biology. We also measure the disciplinary diversity of COVID-19 related papers published from January to December 2020; the disciplinary variety shows an upward trend, while the degree of disciplinary balance shows a downward trend. Meanwhile, the comprehensive index 2Ds demonstrates that the degree of interdisciplinarity in coronavirus field decreases between 1990 and 2019, but it increases in 2020. The results help to map the interdisciplinarity of coronavirus-related research, gaining insight into the degree and history of interdisciplinary cooperation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Xu2021,

title = {Exploring the Interdisciplinary Nature of Precision Medicine：Network Analysis and Visualization},

author = {Xin Xu and Jiming Hu and Xiaoguang Lyu and Huang He and Cheng Xingyu },

doi = {10.2196/23562 },

year  = {2021},

date = {2021-01-11},

urldate = {2021-01-11},

journal = {JMIR Medical Informatics},

abstract = {The aim of this study is to present the nature of interdisciplinary collaboration in precision medicine based on co-occurrences and social network analysis. A total of 7544 studies about precision medicine, published between 2010 and 2019, were collected from the Web of Science database. We analyzed interdisciplinarity with descriptive statistics, co-occurrence analysis, and social network analysis. An evolutionary graph and strategic diagram were created to clarify the development of streams and trends in disciplinary communities. The results indicate that 105 disciplines are involved in precision medicine research and cover a wide range. However, the disciplinary distribution is unbalanced. Current cross-disciplinary collaboration in precision medicine mainly focuses on clinical application and technology-associated disciplines. The characteristics of the disciplinary collaboration network are as follows: (1) disciplinary cooperation in precision medicine is not mature or centralized; (2) the leading disciplines are absent; (3) the pattern of disciplinary cooperation is mostly indirect rather than direct. There are 7 interdisciplinary communities in the precision medicine collaboration network; however, their positions in the network differ. Community 4, with disciplines such as genetics and heredity in the core position, is the most central and cooperative discipline in the interdisciplinary network. This indicates that Community 4 represents a relatively mature direction in interdisciplinary cooperation in precision medicine. Finally, according to the evolution graph, we clearly present the development streams of disciplinary collaborations in precision medicine. We describe the scale and the time frame for development trends and distributions in detail. Importantly, we use evolution graphs to accurately estimate the developmental trend of precision medicine, such as biological big data processing, molecular imaging, and widespread clinical applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gaulda2020,

title = {Analyse en réseau par fouille de données textuelles systématique du concept de psychiatrie personnalisée et de précision},

author = {Christophe Gauld and Jean-Arthur M. Franchi},

url = {http://www.sciencedirect.com/science/article/pii/S0013700620302360},

doi = { https://doi.org/10.1016/j.encep.2020.08.008},

issn = {0013-7006},

year  = {2020},

date = {2020-11-12},

urldate = {2020-11-12},

journal = {L'Encéphale},

abstract = {Objectifs. – La médecine personnalisée et de précision nécessite une clarification des concepts qui y sont rattachés. À notre connaissance, il n’existe pas d’exploration systématique de la littérature portant sur les dimensions et les concepts de la psychiatrie personnalisée et de précision et sur leurs usages dans les domaines neuroscientifiques et génétiques. Cet article propose donc d’explorer les dimensions et les concepts de la psychiatrie personnalisée et de précision.

Méthodes. – Une analyse en réseau par fouille de données textuelles systématique issue d’une revue exhaustive de la littérature internationale autour des termes de “precision psychiatry” et de “personalized psychiatry” a été réalisée. Cette fouille de données textuelles a été représentée sous forme d’un réseau permettant d’analyser les dimensions et les concepts de la psychiatrie personnalisée et de précision. Résultats. – La psychiatrie personnalisée et de précision renvoie à six dimensions retrouvées au sein de l’analyse du réseau textuel. Ces six dimensions correspondent aux domaines scientifiques qui étu- dient la psychiatrie personnalisée et de précision, à savoir : la génétique, la pharmacogénétique, les approches computationnelles, le raffinement des essais thérapeutiques, les biomarqueurs et la stadifica- tion. L’analyse des termes renvoie à un ensemble de concepts hétérogènes.

Conclusions. – L’hétérogénéité retrouvée dans la littérature sur la psychiatrie personnalisée et de précision peut témoigner d’un manque d’un cadre théorique pluraliste et intégratif. Ce cadre de travail pourrait être basé sur un formalisme naturalisant mais non réducteur, conscient des enjeux sociétaux des sciences et de leur implémentation dans les dispositifs de recherche et cliniques de la psychiatrie.

Objectives

The current challenges of psychiatric nosology and semiology are part of an interdisciplinary and integrative framework. The paradigm of the personalized and precision psychiatry proposes to study this discipline according to new approaches and methodologies. Personalized and precision psychiatry therefore requires clarification of its concepts. To our knowledge, there is no systematic exploration of the literature on the application of the concepts of personalized and precision medicine in the field of psychiatry. This article proposes thus to explore the framework of personalized and precision medicine applied to psychiatry.

Methods

We explored the framework of personalized and precision medicine applied to psychiatry by a textual network analysis. Firstly, we performed a systematic text-mining (Natural Language Processing) from an exhaustive review of the international literature with the terms “precision psychiatry” and “personalized psychiatry”. Secondly, this analysis of textual data allowed us to build a textual network which made it possible to visualize the most proximal terms (the most frequently associated in the literature). Finally, we extracted from the network the main dimensions explored in the scientific literature, and we studied the relative importance of each term by analyzing the network centrality. In addition, a brief bibliometric analysis was conducted.

Results

We show that personalized and precision psychiatry refers to six dimensions found in the textual network analysis which correspond to the scientific fields which study personalized and precision psychiatry: genetics, pharmacogenetics, artificial intelligence, therapeutic trials, biomarkers and staging. We explore how each dimension relates to the mechanization of psychiatric disorders. However, precision and personalized psychiatry, which tries to refine the levels of mechanistic explanations for psychiatry, suffers from a conceptual heterogeneity. Indeed, textual analysis also allows us to find terms referring to a set of heterogeneous concepts. Many methodological fields and epistemological concepts are invoked in this literature, without standardization.

Conclusions

The paradox of personalized and precision psychiatry is to associate a strong conceptual heterogeneity with a well-defined mechanistic component. Heterogeneity found in literature on personalized and precision psychiatry testifies to the lack of a pluralist and integrative theoretical framework. This framework could be based on a naturalizing but non-reducing formalism, aware of the societal challenges of the sciences and their implementation in the research and clinical systems of psychiatry.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Deng2020b,

title = {Mapping the interdisciplinarity in information behavior research: a quantitative study using diversity measure and co‐occurrence analysis},

author = {Shengli Deng and Sudi Xia},

doi = {https://doi.org/10.1007/s11192-020-03465-x},

year  = {2020},

date = {2020-04-11},

urldate = {2020-04-11},

abstract = {Information behavior research is an interdisciplinary field in essence due to the investiga- tion of interdisciplinary in previous work. To track the changes in interdisciplinarity of this field, more efforts should be put on basis of previous work. Based on publications searched from Web of Science from 2000 to 2018, we explored the interdisciplinarity of this field drawing on network analysis and diversity measure. Findings showed that although variety of disciplines in this field augmented significantly, the distribution of disciplines is unbal- anced and concentrated on some dominant disciplines such as computer science, engineer- ing, psychology, social science and medicine, etc. Relationships among disciplines have evolved over time and mainly focused on neighboring disciplines instead of distinct disci- plines. Computer science, engineering, psychology, health science and social science func- tion as intermediate disciplines connecting distinct disciplinary groups. Besides, the meas- urement using diversity measure shows that interdisciplinary degree of this field appears to decrease. This study contributes to the evolution and measurement of interdisciplinarity of information behavior research, which has implications for researchers and practitioners in this field.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lyu2020,

title = {Intellectual Structure and Evolutionary Trends of Precision Medicine Research: Coword Analysis},

author = {Xiaoguang Lyu and Jiming Hu and Weiguo Dong and Xin Xu},

url = {https://medinform.jmir.org/2020/2/e11287},

doi = {10.2196/11287},

issn = {2291-9694},

year  = {2020},

date = {2020-02-04},

urldate = {2020-02-04},

journal = {JMIR Med Inform},

volume = {8},

number = {2},

pages = {e11287},

abstract = {Background: Precision medicine (PM) is playing a more and more important role in clinical practice. In recent years, the scale of PM research has been growing rapidly. Many reviews have been published to facilitate a better understanding of the status of PM research. However, there is still a lack of research on the intellectual structure in terms of topics. Objective: This study aimed to identify the intellectual structure and evolutionary trends of PM research through the application of various social network analysis and visualization methods. Methods: The bibliographies of papers published between 2009 and 2018 were extracted from the Web of Science database. Based on the statistics of keywords in the papers, a coword network was generated and used to calculate network indicators of both the entire network and local networks. Communities were then detected to identify subdirections of PM research. Topological maps of networks, including networks between communities and within each community, were drawn to reveal the correlation structure. An evolutionary graph and a strategic graph were finally produced to reveal research venation and trends in discipline communities. Results: The results showed that PM research involves extensive themes and, overall, is not balanced. A minority of themes with a high frequency and network indicators, such as Biomarkers, Genomics, Cancer, Therapy, Genetics, Drug, Target Therapy, Pharmacogenomics, Pharmacogenetics, and Molecular, can be considered the core areas of PM research. However, there were five balanced theme directions with distinguished status and tendencies: Cancer, Biomarkers, Genomics, Drug, and Therapy. These were shown to be the main branches that were both focused and well developed. Therapy, though, was shown to be isolated and undeveloped. Conclusions: The hotspots, structures, evolutions, and development trends of PM research in the past ten years were revealed using social network analysis and visualization. In general, PM research is unbalanced, but its subdirections are balanced. The clear evolutionary and developmental trend indicates that PM research has matured in recent years. The implications of this study involving PM research will provide reasonable and effective support for researchers, funders, policymakers, and clinicians.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Shen2019,

title = {Detecting the Interdisciplinary Nature and Topic Hotspots of Robotics in Surgery: Social Network Analysis and Bibliometric Study},

author = {Lining Shen and Shimin Wang and Wei Dai and Zhiguo Zhang},

doi = {https://doi.org/10.2196/12625},

year  = {2019},

date = {2019-03-19},

urldate = {2019-03-19},

journal = {Journal of Medical Internet Research},

volume = {21},

number = {3},

abstract = {Background: With the widespread application of a robot to surgery, growing literature related to robotics in surgery (RS) documents widespread concerns from scientific researchers worldwide. Although such application is helpful to considerably improve the accuracy of surgery, we still lack the understanding of the multidiscipline-crossing status and topic distribution related to RS. Objective: The aim of this study was to detect the interdisciplinary nature and topic hotspots on RS by analyzing the current publication outputs related to RS. Methods: The authors collected publications related to RS in the last 21 years, indexed by the Web of Science Core Collection. Various bibliometric methods and tools were used, including literature distribution analysis at the country and institution level and interdisciplinary collaboration analysis in the different periods of time. Co-word analysis was performed based on the keywords with high frequency. The temporal visualization bar presented the evolution of topics over time. Results: A total of 7732 bibliographic records related to RS were identified. The United States plays a leading role in the publication output related to RS, followed by Italy and Germany. It should be noted that the Yonsei University in South Korea published the highest number of RS-related publications. Furthermore, the interdisciplinary collaboration is uneven; the number of disciplines involved in each paper dropped from the initial 1.60 to the current 1.31. Surgery; Engineering; Radiology, Nuclear Medicine, and Medical Imaging; and Neurosciences and Neurology are the 4 core disciplines in the field of RS, all of which have extensive cooperation with other disciplines. The distribution of topic hotspots is in imbalanced status, which can be categorized into 7 clusters. Moreover, 3 areas about the evolution of topic were identified, namely (1) the exploration of techniques that make RS implemented, (2) rapid development of robotic systems and related applications in surgery, and (3) application of a robot to excision of tissues or organs targeted at various specific diseases. Conclusions: This study provided important insights into the interdisciplinary nature related to RS, which indicates that the researchers with different disciplinary backgrounds should strengthen cooperation to publish a high-quality output. The research topic hotspots related to RS are relatively scattered, which has begun to turn to the application of RS targeted at specific diseases. Our study is helpful to provide a potential guide to the direction of the field of RS for future research in the field of RS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cambrosio2014big,

title = {Big Data and the Collective Turn in Biomedicine. How Should We Analyze Post-Genomic Practices?},

author = {Alberto Cambrosio and Pascale Bourret and Vololona Rabeharisoa and Michel Callon},

url = {http://www.tecnoscienza.net/index.php/tsj/article/view/178},

year  = {2014},

date = {2014-01-01},

journal = {TECNOSCIENZA: Italian Journal of Science & Technology Studies},

volume = {5},

number = {1},

pages = {11-42},

abstract = {We presently witness a profound transformation of the configuration of biomedical practices, as characterized by an increasingly collective dimension, and by a growing reliance on disruptive technologies that generate large amounts of data. We also witness a proliferation of biomedical databases, often freely accessible on the Web, which can be easily analyzed thanks to network analysis software. In this position paper we discuss how science and technology studies (S&TS) may cope with these developments. In particular, we examine a number of shortcomings of the notion of networks, namely those concerning: (a) the relation between agency and structural analysis; (b) the distinction between network clusters and collectives; (c) the (ac)counting strategies that fuel the networking approach; and (d) the privileged status ascribed to textual documents. This will lead us to reframe the question of the relations between S&TS and biomedical scientists, as big data offer an interesting opportunity for developing new modes of cooperation between the social and the life sciences, while avoiding the dichotomies – between the social and the cognitive, or between texts and practices – that S&TS has successfully managed to discard.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}