Improve Retrieval Performance on Clinical Notes: A Comparison of Four Methods

Abstract

Query expansion is a commonly used approach to improving search results. Specific expansion methods, however, are expected to have different results. We have developed three different expansion methods using knowledge derived from medical thesaurus, medical literature, and clinical notes. Since the three different sources each have strengths and weaknesses, we hypothesized that combining the three sources will lead to better retrieval performance. Evaluation was performed for the 3 different query expansion techniques and an ensemble method on two sets of clinical notes. 11-point interpolated average precisions, MAP, and P(10) scores were calculated which indicate that topic model based expansion has the best results and the predication method the worst. This finding points to the potential of the topic modeling methods as well as the challenge in integrating different knowledge sources.