Structures and Relations of Knowledge Nodes: Exploring a Knowledge Network of Disease from Precision Medicine Research Publications.

Jian Qin, Ning Zou

Research output: Contribution to conferencePaper

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Abstract

The vast amount of DNA sequence and protein data are being explored and linked to diseases as causative factors to support clinical and healthcare decision making. These developments in data-intensive biological sciences and clinical practices raised new questions for knowledge organization systems (KOS), and taxonomies in particular. Sitting at the center of these questions is the lagging of KOS’s capabilities in responding to the rapidly changing and emerging biomedical and disease terms due to the static, hierarchical structures and disconnection with new disease data fin traditional KOSs. This paper reports a pilot study that is designed to uncover and identify the types of knowledge nodes and relationships that can help generalize a framework or model for building a Knowledge Network of Disease, or the New Taxonomy envisaged by the
National Academy of Science. This pilot study examined a sample of biomedical
publications and drew a knowledge map to lay out the main knowledge nodes and their relationships. A preliminary framework for constructing the Knowledge Network of Disease is discussed.
Original languageEnglish (US)
Number of pages11
StatePublished - 2017
EventiConference - Wuhan, China
Duration: Mar 22 2017Mar 25 2017
Conference number: 2017
https://ischools.org/the-iconference/about-the-iconference/iconference-2017-summary/

Conference

ConferenceiConference
CountryChina
CityWuhan
Period3/22/173/25/17
Internet address

Keywords

  • knowledge nodes
  • knowledge modeling
  • content analysis
  • Knowledge Network of Disease

ASJC Scopus subject areas

  • Library and Information Sciences

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