Improving patient record search: A meta-data based approach

Amini, I, Martinez, D, Li, X and Sanderson, M 2016, 'Improving patient record search: A meta-data based approach', Information Processing and Management, vol. 52, no. 2, pp. 258-272.


Document type: Journal Article
Collection: Journal Articles

Attached Files
Name Description MIMEType Size
n2006060358.pdf Submitted Version application/pdf 310.71KB
Title Improving patient record search: A meta-data based approach
Author(s) Amini, I
Martinez, D
Li, X
Sanderson, M
Year 2016
Journal name Information Processing and Management
Volume number 52
Issue number 2
Start page 258
End page 272
Total pages 15
Publisher Elsevier
Abstract The International Classification of Diseases (ICD) is a type of meta-data found in many Electronic Patient Records. Research to explore the utility of these codes in medical Information Retrieval (IR) applications is new, and many areas of investigation remain, including the question of how reliable the assignment of the codes has been. This paper proposes two uses of the ICD codes in two different contexts of search: Pseudo-Relevance Judgments (PRJ) and Pseudo-Relevance Feedback (PRF). We find that our approach to evaluate the TREC challenge runs using simulated relevance judgments has a positive correlation with the TREC official results, and our proposed technique for performing PRF based on the ICD codes significantly outperforms a traditional PRF approach. The results are found to be consistent over the two years of queries from the TREC medical test collection.
Subject Information Retrieval and Web Search
Keyword(s) ICD classification
Information search and retrieval
Information storage and retrieval
Pseudo relevance feedback
DOI - identifier 10.1016/j.ipm.2015.07.005
Copyright notice © 2015 Elsevier Ltd. All rights reserved.
ISSN 0306-4573
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 1 times in Scopus Article | Citations
Altmetric details:
Access Statistics: 72 Abstract Views, 9 File Downloads  -  Detailed Statistics
Created: Thu, 14 Apr 2016, 11:04:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us