Lightweight predicate extraction for patient-level cancer information and ontology development.

Journal: BMC medical informatics and decision making
Published Date: Jul 5, 2017

Abstract

BACKGROUND: Knowledge engineering for ontological knowledgebases is resource and time intensive. To alleviate these issues, especially for novices, automated tools from the natural language domain can assist in the development process of ontologies. We focus towards the development of ontologies for the public health domain and use patient-centric sources from MedlinePlus related to HPV-causing cancers.

Authors

  • Muhammad Amith
    University of Texas Health Science Center.
  • Hsing-Yi Song
    University of Texas School of Biomedical Informatics, 7000 Fannin St Suite 600, Houston, TX, 77030, USA.
  • Yaoyun Zhang
    Alibaba Damo Academy, 969 West Wen Yi Road, Yu Hang District, Hangzhou, Zhejiang, China.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Cui Tao
    The University of Texas Health Science Center at Houston, USA.

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