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An Infobutton For Web 2.0 Clinical Discussions: The Knowledge Linkage Framework

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2 Author(s)
Samuel Alan Stewart ; NICHE Research Group, Faculty of Computer Science, 6050 University Ave., Halifax, NS, Canada, B3H 4R2 ; Syed Sibte Raza Abidi

This paper aims to develop an infobutton to automatically retrieve published papers corresponding to a topic-specific online clinical discussion. The knowledge linkages infobutton is designed to supplement online clinical conversations with pertinent medical literature from Pubmed. The project involves three distinct steps: 1) Clinical messages around a specific problem are grouped together into a thread. 2) These threads are processed using Metamap to link the conversations to keywords from the MeSH lexicon. 3) These keywords are used in a novel search strategy to retrieve a set of papers from Pubmed, which are then returned to the user. A pilot study using the messages from 2007 and 2008, was conducted to compare the knowledge linkage search strategy to a vector space model and extended Boolean model. The knowledge linkage model proved to be significantly better in terms of precision (p = 0.013 and 0.003, respectively) and recall (p = 0.351 and 0.013). Pertinent papers were returned to over 55% of the threads. This approach has demonstrated how clinicians can supplement their peer communications with evidence based research. Future work should focus on how to improve the threading and keyword-mapping strategies.

Published in:

IEEE Transactions on Information Technology in Biomedicine  (Volume:16 ,  Issue: 1 )