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

Funding Information:
This research was supported in part by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (no. 2017R1D1A1B03033721), as well as United States National Institutes of Health (NIH) R01MH105384, and UL1 TR000457-06.

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Health Informatics

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