An integrated web-based system for MEDLINE analysis: A case study of chronic kidney disease

Yi Ling Lin, Wei En Huang, Peir In Liang, Chun Wei Tung

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

Abstract

In the era of big data, medical researchers attempt to utilize some analysis techniques like machine learning and text mining on their large-scale corpora to save valuable labor work and time. Consequently, many data analysis platforms are built to support medical professionals such as Pubtator, GeneWays, BioContext, etc. These platforms are helpful to medical entities recognition and relation extraction, but there is not an integrated platform to support researchers' various needs, and medical projects are isolated from each other, which is hard to be shared and reused. As a result, we present an integrated system containing 'name entity recognition', 'document categorization' and 'association extraction'. Besides, we add the concept of 'socialization' making projects reusable for further analyses. A case study of chronic kidney disease was adopted to indicate the effectiveness of the proposed system.

Original languageEnglish
Title of host publicationProceedings of the 22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society
Subtitle of host publicationAre We Ready?, PACIS 2018
EditorsMotonari Tanabu, Dai Senoo
PublisherAssociation for Information Systems
ISBN (Electronic)9784902590838
Publication statusPublished - 2018
Event22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018 - Yokohama, Japan
Duration: Jun 26 2018Jun 30 2018

Publication series

NameProceedings of the 22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018

Conference

Conference22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018
CountryJapan
CityYokohama
Period6/26/186/30/18

Keywords

  • Association extraction
  • Machine learning
  • Medical analysis
  • Name entity recognition
  • Sharing
  • Text mining

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Lin, Y. L., Huang, W. E., Liang, P. I., & Tung, C. W. (2018). An integrated web-based system for MEDLINE analysis: A case study of chronic kidney disease. In M. Tanabu, & D. Senoo (Eds.), Proceedings of the 22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018 (Proceedings of the 22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018). Association for Information Systems.