IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v119y2019icp196-202.html

Characterising obstructive sleep apnea patients through complex networks

Author

Listed:
  • Zanin, Massimiliano
  • Tuñas, Juan Manuel
  • Bailly, Sébastien
  • Pépin, Jean Louis
  • Hainaut, Pierre
  • Menasalvas, Ernestina

Abstract

Obstructive sleep apnea is a condition whose evolution is poorly understood and difficult to predict, in spite of its high prevalence and serious complications, due to the complexity of its initial symptoms and systemic consequences. In this contribution we discuss the characterisation of a group of patients suffering from this condition through the use of complex networks. Similarity relationships between different subjects are mapped into a network using the recently proposed convergence/divergence formalism. Topological features are then extracted from this structure, and used to feed a classification model forecasting the future evolution of patients after a standard treatment. Results indicate that the complex network approach is able to extract information over and above standard data mining models, thus yielding a new way for the characterisation, and hence for the understanding, of this complex condition.

Suggested Citation

  • Zanin, Massimiliano & Tuñas, Juan Manuel & Bailly, Sébastien & Pépin, Jean Louis & Hainaut, Pierre & Menasalvas, Ernestina, 2019. "Characterising obstructive sleep apnea patients through complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 196-202.
    • Handle: RePEc:eee:chsofr:v:119:y:2019:i:c:p:196-202
    DOI: 10.1016/j.chaos.2018.12.031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077919300086
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2018.12.031?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    2. Nicholas J. Schork, 2015. "Personalized medicine: Time for one-person trials," Nature, Nature, vol. 520(7549), pages 609-611, April.
    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. Huang, Yubo & Dong, Hongli & Zhang, Weidong & Lu, Junguo, 2019. "Stability analysis of nonlinear oscillator networks based on the mechanism of cascading failures," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 5-15.
    2. Aguirre, J. & Almendral, J.A. & Buldú, J.M. & Criado, R. & Gutiérrez, R. & Leyva, I. & Romance, M. & Sendiña-Nadal, I., 2019. "Experimental complexity in physical, social and biological systems," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 200-202.

    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. Li, Chunguang, 2009. "Memorizing morph patterns in small-world neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(2), pages 240-246.
    2. Zheng, Song & Yuan, Liguo, 2019. "Nonperiodically intermittent pinning synchronization of complex-valued complex networks with non-derivative and derivative coupling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 587-605.
    3. Emerson, Isaac Arnold & Amala, Arumugam, 2017. "Protein contact maps: A binary depiction of protein 3D structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 782-791.
    4. Zhenpeng Li & Ling Ma & Simin Chi & Xu Qian, 2022. "Structural Balance under Weight Evolution of Dynamic Signed Network," Mathematics, MDPI, vol. 10(9), pages 1-21, April.
    5. Dan Braha & Yaneer Bar-Yam, 2007. "The Statistical Mechanics of Complex Product Development: Empirical and Analytical Results," Management Science, INFORMS, vol. 53(7), pages 1127-1145, July.
    6. Faedo, Nicolás & García-Violini, Demián & Ringwood, John V., 2021. "Controlling synchronization in a complex network of nonlinear oscillators via feedback linearisation and H∞-control," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    7. Paul Sheridan & Yuichi Yagahara & Hidetoshi Shimodaira, 2008. "A preferential attachment model with Poisson growth for scale-free networks," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 747-761, December.
    8. Ni, Shunjiang & Weng, Wenguo & Zhang, Hui, 2011. "Modeling the effects of social impact on epidemic spreading in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4528-4534.
    9. Xiao‐Bing Hu & Hang Li & XiaoMei Guo & Pieter H. A. J. M. van Gelder & Peijun Shi, 2019. "Spatial Vulnerability of Network Systems under Spatially Local Hazards," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 162-179, January.
    10. Ruiz Vargas, E. & Mitchell, D.G.V. & Greening, S.G. & Wahl, L.M., 2014. "Topology of whole-brain functional MRI networks: Improving the truncated scale-free model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 151-158.
    11. Zheng, Kaiming & Wang, Xiaoyuan & Ni, Debing, 2021. "Reciprocity information and wage personalization," China Economic Review, Elsevier, vol. 68(C).
    12. Yang, Qing-Lin & Wang, Li-Fu & Zhao, Guo-Tao & Guo, Ge, 2020. "A coarse graining algorithm based on m-order degree in complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    13. Igor Belykh & Mateusz Bocian & Alan R. Champneys & Kevin Daley & Russell Jeter & John H. G. Macdonald & Allan McRobie, 2021. "Emergence of the London Millennium Bridge instability without synchronisation," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    14. Berahmand, Kamal & Bouyer, Asgarali & Samadi, Negin, 2018. "A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 41-54.
    15. Zhang, Yun & Liu, Yongguo & Li, Jieting & Zhu, Jiajing & Yang, Changhong & Yang, Wen & Wen, Chuanbiao, 2020. "WOCDA: A whale optimization based community detection algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    16. Soh, Harold & Lim, Sonja & Zhang, Tianyou & Fu, Xiuju & Lee, Gary Kee Khoon & Hung, Terence Gih Guang & Di, Pan & Prakasam, Silvester & Wong, Limsoon, 2010. "Weighted complex network analysis of travel routes on the Singapore public transportation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5852-5863.
    17. Wang, Qingyun & Duan, Zhisheng & Chen, Guanrong & Feng, Zhaosheng, 2008. "Synchronization in a class of weighted complex networks with coupling delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5616-5622.
    18. Cuadra, Lucas & Nieto-Borge, José Carlos, 2024. "Connecting continuous models of quantum systems to complex networks: Application to electron transport in real-world one dimensional van der Waals materials," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    19. Türker, İlker & Çavuşoğlu, Abdullah, 2016. "Detailing the co-authorship networks in degree coupling, edge weight and academic age perspective," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 386-392.
    20. Eva Enns & Margaret Brandeau, 2011. "Inferring model parameters in network-based disease simulation," Health Care Management Science, Springer, vol. 14(2), pages 174-188, June.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:chsofr:v:119:y:2019:i:c:p:196-202. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.