Dongqing Zhu
ABSTRACT
In this paper, we present a medical record search system which is useful for identifying cohorts required in clinical studies. In particular, we propose a query-adaptive weighting method that can dynamically aggregate and score evidence in multiple medical reports (from different hospital departments or from different tests within the same department) of a patient. Furthermore, we explore several informative features for learning our retrieval model.
- A. R. Aronson. Effective mapping of biomedical text to the UMLS metathesaurus: The MetaMap program. Proceedings of AMIA Symposium, pages 17--21, 2001.Google Scholar
- F. Diaz and D. Metzler. Improving the estimation of relevance models using large external corpora. In Proceedings of SIGIR, pages 154--161, 2006. Google ScholarDigital Library
- V. Garla and C. Brandt. Semantic similarity in the biomedical domain: an evaluation across knowledge sources. BMC Bioinformatics, 13:261, 2012.Google ScholarCross Ref
- W. Hersh. Information Retrieval: A Health and Biomedical Perspective. Health Informatics. Springer, 3rd edition, 2009.Google Scholar
- N. Limsopatham, C. Macdonald, R. McCreadie, and I. Ounis. Exploiting term dependence while handling negation in medical search. In Proceedings of SIGIR, pages 1065--1066, 2012. Google ScholarDigital Library
- N. Limsopatham, C. Macdonald, and I. Ounis. Aggregating evidence from hospital departments to improve medical records search. In Proceedings of ECIR, 2013. Google ScholarDigital Library
- N. Limsopatham, C. Macdonald, and I. Ounis. A task-specific query and document representation for medical records search. In Proceedings of ECIR, 2013. Google ScholarDigital Library
- D. Metzler and W. B. Croft. A Markov random field model for term dependencies. Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, page 472, 2005. Google ScholarDigital Library
- D. Sànchez and M. Batet. Semantic similarity estimation in the biomedical domain: An ontology-based information-theoretic perspective. Journal of Biomedical Informatics, 44(5):749--759, 2011. Google ScholarDigital Library
- E. M. Voorhees. DRAFT: Overview of the TREC 2012 medical records track. In TREC, 2012.Google Scholar
- E. M. Voorhees and R. M. Tong. DRAFT: Overview of the TREC 2011 medical records track. In TREC, 2011.Google Scholar
- D. Zhu and B. Carterette. Combining multi-level evidence for medical record retrieval. In Proceedings of SHB, 2012. Google ScholarDigital Library
- D. Zhu and B. Carterette. Exploring evidence aggregation methods and external expansion sources for medical record search. In Proceedings of TREC, 2012.Google Scholar
Index Terms
- An adaptive evidence weighting method for medical record search
Recommendations
Combining multi-level evidence for medical record retrieval
SHB '12: Proceedings of the 2012 international workshop on Smart health and wellbeingThe 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 ...
Medical Record Innovations That Can Improve Physician Productivity
Medical records are the fulcrum of patient care activities. They represent the primary reference point with respect to the patient's medical status and long-term planning. A significant portion of the patient care dollar is invested in the medical ...
Mini Medical Record Application: Annual Register for Flu Shot Vaccinations
This application is an Intranet-based system. A database has been established utilizing patient information on the basis of age, medical diagnosis and employment history. If a health care provider or support staff states that a patient is over 65 years ...
Comments