Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/1830761.1830828acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
short-paper

Genetic algorithm for analysis of abdominal aortic aneurysms in radiology reports

Published: 07 July 2010 Publication History

Abstract

An abdominal aortic aneurysm is a problem in which the wall of the artery that supplies blood to the abdomen and lower extremities expands under pressure or balloons outward. Patients must undergo surgery to repair such an aneurysm, and there is currently no known indicator of long-term success or failure from this surgery. Our work uses a genetic algorithm to analyze radiology reports from these patients to look for common patterns in the language used as well as common features of both successful and unsuccessful surgeries. The results of the genetic algorithm show that patients with complications or unusual characteristics can be identified from a set of radiology reports without the use of search keywords, clustering, categorization, or ontology. This allows medical researchers to search and identify interesting patient records without the need for explicitly defining what "interesting" patient records are.

References

[1]
American College of Radiology (ACR). ACR BI-RADS® - Mammography. 4th Edition. In: ACR Breast Imaging Reporting and Data System, Breast Imaging Atlas. Reston, VA. American College of Radiology; 2003.
[2]
Abdalla, R. M., and Teufel, S. 2006. A bootstrapping approach to unsupervised detection of cue phrase variants. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics (Sydney, Australia). COLING 2006. ACM Press, New York, NY, 2061-2064.
[3]
Cheng, W., Greaves, C. and Warren, M. 2006. From n-gram to skipgram to concgram. International Journal of Corpus Linguistics 11/4: 411--33.
[4]
Fox, C. 1992. "Lexical analysis and stoplists." In Information Retrieval: Data Structures and Algorithms (ed. W.B. Frakes and R. Baeza-Yates), Englewood Cliffs, NJ: Prentice Hall.
[5]
Patton, M.Q. 1990. Qualitative Evaluation and Research Methods, Second Edition. Newbury Park, CA: Sage Publications, Inc.
[6]
Patton, R.M., Beckerman, B.G., and Potok, T.E., 2008. "Analysis of mammography reports using maximum variation sampling." Proceedings of the 4th GECCO Workshop on Medical Applications of Genetic and Evolutionary Computation (MedGEC), Atlanta, USA, July 2008. ACM Press, New York, NY, 2061-2064.
[7]
Patton, R.M., Potok, T.E., Beckerman, B.G., and Treadwell, J.N., 2009. "A Genetic Algorithm for Learning Significant Phrase Patterns in Radiology Reports." Proceedings of the 5th GECCO Workshop on Medical Applications of Genetic and Evolutionary Computation (MedGEC), Montreal, Canada, July 2009. ACM Press, New York, NY, 2061-2064.
[8]
Pirkola, A, Keskustalo, H., Leppänen, E., Känsälä, A.and Järvelin, K. 2002. "Targeted s-gram matching: a novel n-gram matching technique for cross- and monolingual word form variants." Information Research, 7(2) {Available at http://InformationR.net/ir/7-2/paper126.html}
[9]
Porter, M. 1980. "An algorithm for suffix stripping." Program vol. 14, pp. 130-137.
[10]
Porter Stemming Algorithm. Current Feb. 5, 2009. http://www.tartarus.org/~martin/PorterStemmer/
[11]
Raghavan, V.V., and Wong, S.K.M. 1986. "A critical analysis of vector space model for information retrieval." Journal of the American Society for Information Science, Vol.37 (5), p. 279--87.
[12]
Salton, G. 1983. Introduction to Modern Information Retrieval. McGraw-Hill.

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
GECCO '10: Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
July 2010
1496 pages
ISBN:9781450300735
DOI:10.1145/1830761
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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2010

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. abdominal aortic aneurysm
  2. genetic algorithm
  3. medical knowledge discovery
  4. natural language processing

Qualifiers

  • Short-paper

Conference

GECCO '10
Sponsor:

Acceptance Rates

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 107
    Total Downloads
  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 22 Nov 2024

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media