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Community detector on symptom networks with applications to fatty liver disease

Author

Listed:
  • Li, Cong
  • Wang, Wenjing
  • Li, Jingya
  • Xu, Jiatuo
  • Li, Xiang

Abstract

Community detection separates nodes into communities where nodes are densely connected. Here we apply the community detection to find the strongly related nodes in a network, by introducing the local information of nodes, such as the weight strength of nodes and the link weights into the BGLL community detection. We have improved the BGLL community detection algorithms with three methods and compared their qualities of finding the relations between the symptoms and severity levels in symptom networks. The high accuracy of an improved BGLL algorithm in finding the strong relations between the symptoms and the severity levels are verified in the symptom networks of the fatty liver disease. The relations that we have observed motivate us to find a small set of representative symptoms for each severity level of the fatty liver disease. Besides, we achieve the changing trends of the representative symptoms in the fatty liver disease. The results of the representative symptoms and changing trends of the representative symptoms in FLD are supported by clinical diagnosis.

Suggested Citation

  • Li, Cong & Wang, Wenjing & Li, Jingya & Xu, Jiatuo & Li, Xiang, 2019. "Community detector on symptom networks with applications to fatty liver disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    • Handle: RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119307861
    DOI: 10.1016/j.physa.2019.121328
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    Citations

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    Cited by:

    1. Xinyu Wang & Liang Zhao & Ning Zhang & Liu Feng & Haibo Lin, 2022. "Stability of China's Stock Market: Measure and Forecast by Ricci Curvature on Network," Papers 2204.06692, arXiv.org.
    2. Haseeb Tariq & Marwan Hassani, 2023. "Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions," Papers 2309.13662, arXiv.org.
    3. Pierre Bertrand & Michel Broniatowski & Jean-François Marcotorchino, 2022. "Independence versus indetermination: basis of two canonical clustering criteria," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 1069-1093, December.
    4. Lai, Xin & Bai, Shuliang & Lin, Yong, 2022. "Normalized discrete Ricci flow used in community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).

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