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Improving health records search using multiple query expansion collections

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2 Author(s)
Donqqing Zhu ; Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA ; Ben Carterette

The increasing prevalence of electronic health records (EHR), along with the needs for enhanced clinical care, presents new challenges to information retrieval (IR). Many clinical decision-making tasks following the philosophy of Evidence-Based Medicine (EBM) rely on the ability to find relevant health records and gather sufficient clinical evidence under severe time constraints. In this work, we present a system built upon statistical IR methods for searching flat-text health records (i.e. the doctors' notes sections of EHR) for patients with particular conditions specified via a keyword query. In particular, we use multiple external repositories for query expansion, and introduce two novel model weighting methods. Cross-validation results show that our system improves a strong baseline by 30% on mean average precision (MAP), and has a promising overall performance when compared with a manual system doing the same task.

Published in:

Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on

Date of Conference:

4-7 Oct. 2012