Abstract—We present an approach of selecting medical
literature for the purpose of supporting clinical diagnostic
decision. The proposed approach is based on link analysis in the
weighted keywords network. The keywords in the network are
extracted from the keywords lists in the articles, the Mesh
lexicon and acronyms, with which the full relation of keywords
and articles (the link network) is built. In this paper we
introduced in details how to extract the collection of valid
sentences and diagnosis-related keywords based on the
keywords co-occurrence analysis and existing description of
symptoms. The paper also lays out the detailed process of
measuring the relevance between keywords and articles with
link analysis in the weighted keywords network. Finally, we
report some related experiments and the results of user
evaluations.
Index Terms—Clinical decision support, link analysis,
weighted keyword network, medical information retrieval.
Ying Sun is with the University at Buffalo, the State University of New
York, %34 Baldy Hall, Buffalo, NY, 14260 USA (e-mail:
sun3@buffalo.edu).
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Cite: Ying Sun, "Literature Recommendation to Support Clinical Diagnostic Decision — An Approach Based on Link Analysis in the Weighted Keywords Network," International Journal of Knowledge Engineering vol. 1, no. 2, pp. 134-140, 2015.
