A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improving the estimation of relevance models using large external corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Linear feature-based models for information retrieval
Information Retrieval
Search Engines: Information Retrieval in Practice
Search Engines: Information Retrieval in Practice
Journal of Biomedical Informatics
SHB 2012: international workshop on smart health and wellbeing
Proceedings of the 21st ACM international conference on Information and knowledge management
An adaptive evidence weighting method for medical record search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Inferring conceptual relationships to improve medical records search
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
Learning to handle negated language in medical records search
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Learning to selectively rank patients' medical history
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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The increasing prevalence of electronic health records containing rich information about a patient's health and physical condition has the potential to transform research in health and medicine. In this work, we present a health record search system for finding patients matching certain inclusion criteria (specified as keyword queries) for clinical studies. In particular, our system aggregates multi-level evidence and combines proven statistical IR models, both in an innovative way, and achieves a 20% MAP (mean average precision) improvement over a strong baseline. Moreover, our cross-validation results show that the overall performance of our system is comparable to other top-performing systems on the same task.