Uncovering 3D bioprinting research trends: A keyword network mapping analysis

García-García, Leonardo A.; Rodríguez-Salvador, Marisela

doi:10.18063/ijb.v4i2.147

Cited by 9 publications

(4 citation statements)

References 21 publications

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“…A Cohen's kappa (κ) of 0.62 was obtained for the agreement on the author name disambiguation. Values from 0.61 to 0.8 are ranked as Good [36]. A collaboration was observed in 93% of the authors, being 792 the total number of connections in the map.…”

Section: Resultsmentioning

confidence: 99%

“…The ten most cited papers identified through this search were selected, as they have been acknowledged as referents for the topic. Table 1, García-García [36], shows the ten articles that formed the first set of documents. These papers were used to identify the keywords to form the search queries.…”

Section: Methodsmentioning

confidence: 99%

“…Comparison of the top ten cited papers from Scopus obtained from the search of`bioprinting' and the developed search query in titles, abstracts, or keywords Top ten results using the keyword bioprinting[36] Top ten articles using the developed search string…”

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confidence: 99%

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Disclosing Main authors and Organisations collaborations in bioprinting through network maps analysis

García-García

Rodríguez-Salvador

2020

J Biomed Semant

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Background: Scientific activity for 3D bioprinting has increased over the past years focusing mainly on fully functional biological constructs to overcome issues related to organ transplants. This research performs a scientometric analysis on bioprinting based on a competitive technology intelligence (CTI) cycle, which assesses scientific documents to establish the publication rate of science and technology in terms of institutions, patents or journals. Although analyses of publications can be observed in the literature, the identification of the most influential authors and affiliations has not been addressed. This study involves the analysis of authors and affiliations, and their interactions in a global framework. We use network collaboration maps and Betweenness Centrality (BC) to identify of the most prominent actors in bioprinting, enhancing the CTI analysis. Results: 2088 documents were retrieved from Scopus database from 2007 to 2017, disclosing an exponential growth with an average publication increase of 17.5% per year. A threshold of five articles with ten or more cites was established for authors, while the same number of articles but cited five or more times was set for affiliations. The author with more publications was Atala A. (36 papers and a BC = 370.9), followed by Khademhosseini A. (30 documents and a BC = 2104.7), and Mironov (30 documents and BC = 2754.9). In addition, a small correlation was observed between the number of collaborations and the number of publications. Furthermore, 1760 institutions with a median of 10 publications were found, but only 20 within the established threshold. 30% of the 20 institutions had an external collaboration, and institutions located in and close to the life science cluster in Massachusetts showed a strong cooperation. The institution with more publications was the Harvard Medical School, 61 publications, followed by the Brigham and Women's hospital, 46 papers, and the Massachusetts Institute of Technology with 37 documents. Conclusions: Network map analysis and BC allowed the identification of the most influential authors working on bioprinting and the collaboration between institutions was found limited. This analysis of authors and affiliations and their collaborations offer valuable information for the identification of potential associations for bioprinting researches and stakeholders.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Disclosing Main authors and Organisations collaborations in bioprinting through network maps analysis

García-García

Rodríguez-Salvador

2020

J Biomed Semant

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“…20 Although scientists can now bioprint only simple structures like skin or cornea, it is expected that sophisticated structures, and even functional organs, will be bioprinted in the future. 21 In these three domains, it is possible to take advantage of the human body's plasticity to generate therapies, which characterises the field of regenerative medicine. 22 The question that arises is: considering the ways in which biomodifying technologies have been developed and appropriated, have principles of good governance been safeguarded?…”

Section: Biomodifying Technologiesmentioning

confidence: 99%

Patent power in biomedical innovation: Technology governance in biomodifying technologies

Bicudo

Morrison

et al. 2022

World Intellectual Property

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Biomedical innovation is often rewarded by exclusive proprietary rights such as patents. In the case of gene editing, induced pluripotent stem cells, and three‐dimensional (3D) bioprinting (here described as biomodifying technologies), the limitations of the patent system come into stark relief, generating both technical and political doubts. Generally, political and technological limitations are supposed to be solved with so‐called good governance, based on some principles. We focus on three of such governance principles (participation, accountability, and transparency) to show how they have been weakened, instead of strengthened, by the current patent system. We demonstrate that although patent applications are submitted by both public and private players, the latter have imposed a growing dominance in gene editing, induced pluripotent stem cells, and 3D bioprinting, disseminating their aggressive and exclusive strategies. As a consequence, a logic of experimentality tends to prevail where the three fundamental governance principles fail to be enacted.

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30th Anniversary of Applied Intelligence: A combination of bibliometrics and thematic analysis using SciMAT

et al. 2021

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Applied Intelligence is one of the most important international scientific journals in the field of artificial intelligence. From 1991, Applied Intelligence has been oriented to support research advances in new and innovative intelligent systems, methodologies, and their applications in solving real-life complex problems. In this way, Applied Intelligence hosts more than 2,400 publications and achieves around 31,800 citations. Moreover, Applied Intelligence is recognized by the industrial, academic, and scientific communities as a source of the latest innovative and advanced solutions in intelligent manufacturing, privacy-preserving systems, risk analysis, knowledge-based management, modern techniques to improve healthcare systems, methods to assist government, and solving industrial problems that are too complex to be solved through conventional approaches. Bearing in mind that Applied Intelligence celebrates its 30th anniversary in 2021, it is appropriate to analyze its bibliometric performance, conceptual structure, and thematic evolution. To do that, this paper conducts a bibliometric performance and conceptual structure analysis of Applied Intelligence from 1991 to 2020 using SciMAT. Firstly, the performance of the journal is analyzed according to the data retrieved from Scopus, putting the focus on the productivity of the authors, citations, countries, organizations, funding agencies, and most relevant publications. Finally, the conceptual structure of the journal is analyzed with the bibliometric software tool SciMAT, identifying the main thematic areas that have been the object of research and their composition, relationship, and evolution during the period analyzed.

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Uncovering 3D bioprinting research trends: A keyword network mapping analysis

Cited by 9 publications

References 21 publications

Disclosing Main authors and Organisations collaborations in bioprinting through network maps analysis

Disclosing Main authors and Organisations collaborations in bioprinting through network maps analysis

Patent power in biomedical innovation: Technology governance in biomodifying technologies

30th Anniversary of Applied Intelligence: A combination of bibliometrics and thematic analysis using SciMAT

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