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Automatic patient search for breast cancer clinical trials using free-text medical reports

Published: 11 November 2010 Publication History

Abstract

The purpose of this work is to develop algorithms to automatically identify qualified patients for breast cancer clinical trials from free-text medical reports. Specifically, we developed an algorithm, called subtree match, that achieves this by finding structural patterns in free-text patient report sentences that are consistent with given trial criteria. Experimental results indicate that this technique is effective and performs better than several competing techniques. Our work is useful in two respects. First, it can potentially increase the efficiency and reduce the cost of the patient enrollment process. Second, it can be extended/adapted to the clinical trials of other diseases

References

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A Wilcox, K Natarajan, C Weng, "Using personal health records for automated clinical trials recruitment: the ePaIRing model," Proc. AMIA Translational Bioinformatics Summit 2009, March 15-17, 2009, San Francisco, CA. pp. 136--140.
[2]
J. Kamal et al, "Using an information warehouse to screen patients for clinical trials: a prototype," Proc. 2005 AMIA Annual Symposium. p. 1004, 2005.
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Lonsdale et al., "Assessing clinical trial eligibility with logic expression queries," Data & Knowledge Engineering, Volume 66, Issue 1, pp 3--17, July 2008.
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L. Rokach et al., "Information retrieval system for medical narrative reports," Lecture Notes in Computer Science, Vol 3055, pp. 217--228, Springer, 2004
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B. MacCartney et al., "Learning to recognize features of valid textual entailment," Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL 2006), 2006.
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B. MacCartney and C. Manning, "Modeling semantic containment and exclusion in natural language inference," The 22nd International Conference on Computational Linguistics (Coling-08), Manchester, UK, August 2008.
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A. Hickl et al., "Recognizing textural entailment with LCC's Groundhog System," Proc. 2nd PASCAL Challenges Workshop on Recognizing Textural Entailment, 2006.
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A. Hickl and J. Bensley, "A discourse commitment-based framework for recognizing textual entailment," Proc. ACL, 2007.
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D. Jurafsky and J. J. Martin, Speech and Language Processing, 2nd Edition, Prentice-Hall, 2008.
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R. A. Aronson, "Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program," Proceedings of 2001 AMIA Symposium, pp. 17--21.
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Stanford software: parsing and subtree search. http://nlp.stanford.edu/software/lex-parser.shtml and http://nlp.stanford.edu/software/tregex.shtml
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A reference about word net. http://search.cpan.org/dist/WordNet-Similarity/
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C. Manning, P. Raghavan, and H. Schutze, Introduction to Information Retrieval, Cambridge University Press, 2008.
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Cited By

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  • (2013)Automatic Patient Search Using Bernoulli ModelProceedings of the 2013 IEEE International Conference on Healthcare Informatics10.1109/ICHI.2013.80(517-522)Online publication date: 9-Sep-2013
  • (2012)Automated search for patient recordsProceedings of the 2nd ACM SIGHIT International Health Informatics Symposium10.1145/2110363.2110442(691-696)Online publication date: 28-Jan-2012

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  1. Automatic patient search for breast cancer clinical trials using free-text medical reports

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    cover image ACM Other conferences
    IHI '10: Proceedings of the 1st ACM International Health Informatics Symposium
    November 2010
    886 pages
    ISBN:9781450300308
    DOI:10.1145/1882992
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 11 November 2010

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    Author Tags

    1. breast cancer
    2. clinical trials
    3. patient search
    4. subtree

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    IHI '10: ACM International Health Informatics Symposium
    November 11 - 12, 2010
    Virginia, Arlington, USA

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    • (2013)Automatic Patient Search Using Bernoulli ModelProceedings of the 2013 IEEE International Conference on Healthcare Informatics10.1109/ICHI.2013.80(517-522)Online publication date: 9-Sep-2013
    • (2012)Automated search for patient recordsProceedings of the 2nd ACM SIGHIT International Health Informatics Symposium10.1145/2110363.2110442(691-696)Online publication date: 28-Jan-2012

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