Diversity-aware retrieval of medical records

• The medical ontologyis used to address ambiguities in a medical query.
• Multiple sub-queries are constructed from the original medical query.
• The medical record relevance and novelty are combined together for ranking.
• The empirical experiments demonstrate the effectiveness of the approach.
• A pilot study onitsreal-world application is given for better medical service.

The widely adoption of Electronic Medical Records (EMRs) causes an explosive growth of the medical and clinical data. It makes the medical search technologies become critical to find useful patient information in the large medical dataset. However, the high quality medical search is a challenging task, in particular due to the inherent complexity and ambiguity of medical terminology. In this paper, by exploiting the uncertainty in ambiguous medical queries, we propose a novel semantic-based approach to achieve the diversity-aware retrieval of EMRs, i.e., both the relevance and novelty are considered for EMR ranking. With the support of medical domain ontologies, we first mine all the potential semantics (concepts and relations between them) from a user query and consume them to model the multiple query aspects. Then, we propose a novel diversification strategy, which considers not only the aspect importance but also the aspect similarity, to perform the diversity-aware EMR ranking. A real-world pilot study, which utilizes the proposed medical search approach to improve the second use of the EMRs, is reported. We believe that our experience can serve as an important reference for the development of similar applications in a medical data utilization and sharing environment.

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