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Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed

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  • Loet Leydesdorff
  • Daniele Rotolo
  • Ismael Rafols

Abstract

Multiple perspectives on the nonlinear processes of medical innovations can be distinguished and combined using the Medical Subject Headings (MeSH) of the MEDLINE database. Focusing on three main branches—“diseases,” “drugs and chemicals,” and “techniques and equipment”—we use base maps and overlay techniques to investigate the translations and interactions and thus to gain a bibliometric perspective on the dynamics of medical innovations. To this end, we first analyze the MEDLINE database, the MeSH index tree, and the various options for a static mapping from different perspectives and at different levels of aggregation. Following a specific innovation (RNA interference) over time, the notion of a trajectory which leaves a signature in the database is elaborated. Can the detailed index terms describing the dynamics of research be used to predict the diffusion dynamics of research results? Possibilities are specified for further integration between the MEDLINE database on one hand, and the Science Citation Index and Scopus (containing citation information) on the other.
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  • Loet Leydesdorff & Daniele Rotolo & Ismael Rafols, 2012. "Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2239-2253, November.
    • Handle: RePEc:bla:jinfst:v:63:y:2012:i:11:p:2239-2253
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    Cited by:

    1. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.
    2. Ryosuke L. Ohniwa & Aiko Hibino, 2019. "Generating process of emerging topics in the life sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1549-1561, December.
    3. Petersen, Alexander M. & Rotolo, Daniele & Leydesdorff, Loet, 2016. "A triple helix model of medical innovation: Supply, demand, and technological capabilities in terms of Medical Subject Headings," Research Policy, Elsevier, vol. 45(3), pages 666-681.
    4. Daniele Rotolo & Loet Leydesdorff, 2014. "Matching MEDLINE/PubMed Data with Web of Science (WOS): A Routine in R language," SPRU Working Paper Series 2014-14, SPRU - Science Policy Research Unit, University of Sussex Business School.
    5. Nicola Grassano & Daniele Rotolo & Joshua Hutton & Frédérique Lang & Michael M. Hopkins, 2017. "Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 999-1017, April.
    6. Yaqub, Ohid & Coburn, Josie & Moore, Duncan A.Q., 2023. "Knowledge spillovers from HIV research-funding," SocArXiv gcuhn, Center for Open Science.
    7. Kevin W. Boyack, 2017. "Thesaurus-based methods for mapping contents of publication sets," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1141-1155, May.
    8. Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
    9. Ávila-Robinson, Alfonso & Islam, Nazrul & Sengoku, Shintaro, 2019. "Co-evolutionary and systemic study on the evolution of emerging stem cell-based therapies," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 324-339.
    10. Loet Leydesdorff & Jordan A. Comins & Aaron A. Sorensen & Lutz Bornmann & Iina Hellsten, 2016. "Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2077-2091, December.
    11. Seolmin Yang & So Young Kim, 2023. "Knowledge-integrated research is more disruptive when supported by homogeneous funding sources: a case of US federally funded research in biomedical and life sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3257-3282, June.
    12. Timothy D. Bowman & Andrew Tsou & Chaoqun Ni & Cassidy R. Sugimoto, 2014. "Post-interdisciplinary frames of reference: exploring permeability and perceptions of disciplinarity in the social sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1695-1714, December.
    13. Torres-Salinas, Daniel & Rodríguez-Sánchez, Rosa & Robinson-García, Nicolás & Fdez-Valdivia, J. & García, J.A., 2013. "Mapping citation patterns of book chapters in the Book Citation Index," Journal of Informetrics, Elsevier, vol. 7(2), pages 412-424.
    14. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    15. Goldman, Alyssa W., 2014. "Conceptualizing the interdisciplinary diffusion and evolution of emerging fields: The case of systems biology," Journal of Informetrics, Elsevier, vol. 8(1), pages 43-58.
    16. Ryosuke L. Ohniwa & Kunio Takeyasu & Aiko Hibino, 2022. "Researcher dynamics in the generation of emerging topics in life sciences and medicine," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 871-884, February.
    17. Loet Leydesdorff, 2013. "Statistics for the dynamic analysis of scientometric data: the evolution of the sciences in terms of trajectories and regimes," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 731-741, September.
    18. Daniele Rotolo & Ismael Rafols & Michael Hopkins & Loet Leydesdorff, 2014. "Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies," SPRU Working Paper Series 2014-10, SPRU - Science Policy Research Unit, University of Sussex Business School.
    19. Lv, Yanhua & Ding, Ying & Song, Min & Duan, Zhiguang, 2018. "Topology-driven trend analysis for drug discovery," Journal of Informetrics, Elsevier, vol. 12(3), pages 893-905.
    20. Gaetan de Rassenfosse & Kyle Higham & Orion Penner, 2022. "Scientific rewards for biomedical specialization are large and persistent," Working Papers 19, Chair of Science, Technology, and Innovation Policy.
    21. Ma, Jing & Abrams, Natalie F. & Porter, Alan L. & Zhu, Donghua & Farrell, Dorothy, 2019. "Identifying translational indicators and technology opportunities for nanomedical research using tech mining: The case of gold nanostructures," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 767-775.
    22. Takano, Yasutomo & Kajikawa, Yuya, 2019. "Extracting commercialization opportunities of the Internet of Things: Measuring text similarity between papers and patents," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 45-68.

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