The detection of Chinese herbal rules for Gastro-esophageal reflux disease by data mining

Dan He, Meiling Yao, Miao Jiang, Chi Zhang, Aiping LYU*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

To explore the regularity of clinical medication of Gastro-esophageal reflux disease (GERD) through text mining approach. Literatures on GERD in SinoMed(Chinese biomedical literature service system) were collected. Results: BANXIA, CHAIHU and HUANGLIAN were commonly used Chinese herbs in sequence from high to low, the network of Chinese herbs, symptoms and patterns could be established. Conclusion: The commonly used Chinese Herbs are coincided with the treatment rules of regulating the function of liver and stomach as well as adjusting cold and heat and the networks are corresponded with each other in treating GERD and could be verified through text mining approach.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
EditorsHuiru Zheng, Xiaohua Tony Hu, Yadong Wang, Jin-Kao Hao, David Gilbert, Daniel Berrar, Kwang-Hyun Cho, Werner Dubitzky
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages35-36
Number of pages2
ISBN (Electronic)9781479956692
DOIs
Publication statusPublished - 29 Dec 2014
Event2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 - Belfast, United Kingdom
Duration: 2 Nov 20145 Nov 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014

Conference

Conference2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
Country/TerritoryUnited Kingdom
CityBelfast
Period2/11/145/11/14

Scopus Subject Areas

  • Biomedical Engineering
  • Health Informatics

User-Defined Keywords

  • Gastro-esophageal reflux disease
  • Regularity of clinical medication
  • Text mining

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