Comparing sex-specific association networks of chronic medical conditions

Min Hyung Kim, Yongjun Zhu, Samprit Banerjee, Lauren Evans, Yiye Zhang, Fei Wang, Sang Min Park, Jyotishman Pathak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sex (i.e., male or female) has a significant influence on physiologic and pathologic processes, and therefore, studying sex-specific distributions of medical conditions is a rationally important step in the analysis of clinical data. In this study, using data from the Korean National Health Insurance Services, we systemically compare sex-specific association networks of chronic medical conditions, and present a network-theoretic analysis with a rewire metric to explore all possible pairs of chronic medical conditions that differentially cooccur in male and female population. Given that sex appears to interact with the co-occurrence of these chronic conditions, future research may wish to examine these conditions separately in males and females.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages368-370
Number of pages3
ISBN (Electronic)9781538653777
DOIs
Publication statusPublished - 2018 Jul 24
Event6th IEEE International Conference on Healthcare Informatics, ICHI 2018 - New York, United States
Duration: 2018 Jun 42018 Jun 7

Publication series

NameProceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018

Conference

Conference6th IEEE International Conference on Healthcare Informatics, ICHI 2018
Country/TerritoryUnited States
CityNew York
Period18/6/418/6/7

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Health Informatics

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