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{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{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}

}