Cohort Shepherd: Discoving Cohort Traits from Hospital Visits

This paper describes the system created by the University of Texas at Dallas for contentbased medical record retrieval submitted to the TREC 2011 Medical Records Track. Our system builds a query by extracting keywords from a given topic using a Wikipedia-based approach we use regular expressions to extract age, gender, and negation requirements. Each query is then expanded by relying on UMLS, SNOMED, Wikipedia, and PubMed Co-occurrence data for retrieval. Four runs were submitted: two based on Lucene with varying scoring methods, and two based on a hybrid approach with varying negation detection techniques. Our highest scoring submission achieved a MAP score of 40.8.