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Title:Structures and relations of knowledge nodes: Exploring a knowledge network of disease from precision medicine research publications
Author(s):Qin, Jian; Zou, Ning
Subject(s):Knowledge nodes
Knowledge network of disease
Content analysis
Knowledge modeling
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.
Issue Date:2017
Publisher:iSchools
Citation Info:Qin, J., & Zou, N. (2017). Structures and Relations of Knowledge Nodes: Exploring a Knowledge Network of Disease from Precision Medicine Research Publications. In iConference 2017 Proceedings (pp. 56–65). https://doi.org/10.9776/17009
Series/Report:iConference 2017 Proceedings
Genre:Conference Paper/Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/96684
DOI:https://doi.org/10.9776/17009
Rights Information:Copyright 2017 Jian Qin and Ning Zou
Date Available in IDEALS:2017-07-27


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