IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v392y2013i23p6084-6089.html
   My bibliography  Save this article

The networks from medical knowledge and clinical practice have small-world, scale-free, and hierarchical features

Author

Listed:
  • Tachimori, Yutaka
  • Iwanaga, Hiroaki
  • Tahara, Takashi

Abstract

Here, we constructed and analyzed a network (henceforth, “medical knowledge network”) derived from a commonly used medical text. We show that this medical knowledge network has small-world, scale-free, and hierarchical features. We then constructed a network from data from a hospital information system that reflected actual clinical practice and found that this network also had small-world, scale-free, and hierarchical features. Moreover, we found that both the diagnosis frequency distribution of the hospital network and the diagnosis degree distribution of the medical knowledge network obeyed a similar power law. These findings suggest that the structure of clinical practice may emerge from the mutual influence of medical knowledge and clinical practice, and that the analysis of a medical knowledge network may facilitate the investigation of the characteristics of medical practice.

Suggested Citation

  • Tachimori, Yutaka & Iwanaga, Hiroaki & Tahara, Takashi, 2013. "The networks from medical knowledge and clinical practice have small-world, scale-free, and hierarchical features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6084-6089.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:23:p:6084-6089
    DOI: 10.1016/j.physa.2013.07.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437113006572
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2013.07.047?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Markošová, Mária, 2008. "Network model of human language," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 661-666.
    2. Fink, Waltraud & Lipatov, Vilen & Konitzer, Martin, 2009. "Diagnoses by general practitioners: Accuracy and reliability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 784-793, October.
    3. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    4. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    5. Barabási, Albert-László & Ravasz, Erzsébet & Vicsek, Tamás, 2001. "Deterministic scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 559-564.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Samuel Zanferdini Oliva & Livia Oliveira-Ciabati & Denise Gazotto Dezembro & Mário Sérgio Adolfi Júnior & Maísa Carvalho Silva & Hugo Cesar Pessotti & Juliana Tarossi Pollettini, 2021. "Text structuring methods based on complex network: a systematic review," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1471-1493, February.
    2. Jiang, Jingchi & Zheng, Jichuan & Zhao, Chao & Su, Jia & Guan, Yi & Yu, Qiubin, 2016. "Clinical-decision support based on medical literature: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 42-54.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guillaume, Jean-Loup & Latapy, Matthieu, 2006. "Bipartite graphs as models of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 795-813.
    2. Laurienti, Paul J. & Joyce, Karen E. & Telesford, Qawi K. & Burdette, Jonathan H. & Hayasaka, Satoru, 2011. "Universal fractal scaling of self-organized networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3608-3613.
    3. Wen, Xiangxi & Tu, Congliang & Wu, Minggong, 2018. "Node importance evaluation in aviation network based on “No Return” node deletion method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 546-559.
    4. Selen Onel & Abe Zeid & Sagar Kamarthi, 2011. "The structure and analysis of nanotechnology co-author and citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 119-138, October.
    5. Hayato Goto & Hideki Takayasu & Misako Takayasu, 2017. "Estimating risk propagation between interacting firms on inter-firm complex network," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-12, October.
    6. Zhang, Zhongzhi & Rong, Lili & Comellas, Francesc, 2006. "High-dimensional random Apollonian networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 610-618.
    7. P.B., Divya & Lekha, Divya Sindhu & Johnson, T.P. & Balakrishnan, Kannan, 2022. "Vulnerability of link-weighted complex networks in central attacks and fallback strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    8. Foti, Nicholas J. & Pauls, Scott & Rockmore, Daniel N., 2013. "Stability of the World Trade Web over time – An extinction analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1889-1910.
    9. Caccioli, Fabio & Farmer, J. Doyne & Foti, Nick & Rockmore, Daniel, 2015. "Overlapping portfolios, contagion, and financial stability," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 50-63.
    10. Tsuchiya, Masa & Selvarajoo, Kumar & Piras, Vincent & Tomita, Masaru & Giuliani, Alessandro, 2009. "Local and global responses in complex gene regulation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1738-1746.
    11. Sun, Lanfang & Jiang, Lu & Li, Menghui & He, Dacheng, 2006. "Statistical analysis of gene regulatory networks reconstructed from gene expression data of lung cancer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 663-671.
    12. Dong, Gaogao & Tian, Lixin & Du, Ruijin & Fu, Min & Stanley, H. Eugene, 2014. "Analysis of percolation behaviors of clustered networks with partial support–dependence relations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 370-378.
    13. Yuji Yamamoto & Keiko Yokoyama, 2011. "Common and Unique Network Dynamics in Football Games," PLOS ONE, Public Library of Science, vol. 6(12), pages 1-6, December.
    14. Tony H. Grubesic & Timothy C. Matisziw & Alan T. Murray & Diane Snediker, 2008. "Comparative Approaches for Assessing Network Vulnerability," International Regional Science Review, , vol. 31(1), pages 88-112, January.
    15. LaRocca, Sarah & Guikema, Seth D., 2015. "Characterizing and predicting the robustness of power-law networks," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 157-166.
    16. Pagani, Giuliano Andrea & Aiello, Marco, 2013. "The Power Grid as a complex network: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2688-2700.
    17. N. Foti & S. Pauls & Daniel N. Rockmore, 2011. "Stability of the World Trade Web over Time - An Extinction Analysis," Papers 1104.4380, arXiv.org, revised May 2011.
    18. John Platig & Peter J Castaldi & Dawn DeMeo & John Quackenbush, 2016. "Bipartite Community Structure of eQTLs," PLOS Computational Biology, Public Library of Science, vol. 12(9), pages 1-17, September.
    19. Blagus, Neli & Šubelj, Lovro & Bajec, Marko, 2012. "Self-similar scaling of density in complex real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2794-2802.
    20. Biggiero, Lucio & Angelini, Pier Paolo, 2015. "Hunting scale-free properties in R&D collaboration networks: Self-organization, power-law and policy issues in the European aerospace research area," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 21-43.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:392:y:2013:i:23:p:6084-6089. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.