Causal relations of health indices inferred statistically using the DirectLiNGAM algorithm from big data of Osaka prefecture health checkups.
Causal relations among many statistical variables have been assessed using a Linear non-Gaussian Acyclic Model (LiNGAM). Using access to large amounts of health checkup data from Osaka prefecture obtained during the six fiscal years of years 2012-2017, we applied the DirectLiNGAM algorithm as a tria...
Main Authors: | Jun'ichi Kotoku, Asuka Oyama, Kanako Kitazumi, Hiroshi Toki, Akihiro Haga, Ryohei Yamamoto, Maki Shinzawa, Miyae Yamakawa, Sakiko Fukui, Keiichi Yamamoto, Toshiki Moriyama |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0243229 |
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