Prognosis of Breast Cancer Using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Ludwig:2010:KES,
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title = "Prognosis of Breast Cancer Using Genetic Programming",
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author = "Simone A. Ludwig and Stefanie Roos",
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booktitle = "14th International Conference on Knowledge-Based and
Intelligent Information and Engineering Systems (KES
2010), Part {IV}",
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year = "2010",
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editor = "Rossitza Setchi and Ivan Jordanov and
Robert J. Howlett and Lakhmi C. Jain",
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volume = "6279",
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series = "Lecture Notes in Computer Science",
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pages = "536--545",
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address = "Cardiff, UK",
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month = sep # " 8-10",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-15383-9",
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DOI = "doi:10.1007/978-3-642-15384-6_57",
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size = "10 pages",
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bibdate = "2010-12-02",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/kes/kes2010-4.html#LudwigR10",
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abstract = "Worldwide, breast cancer is the second most common
type of cancer after lung cancer and the fifth most
common cause of cancer death. In 2004, breast cancer
caused 519,000 deaths worldwide. In order to reduce the
cancer deaths and thereby increasing the survival rates
an automatic approach is necessary to aid physicians in
the prognosis of breast cancer. This paper investigates
the prognosis of breast cancer using a machine learning
approach, in particular genetic programming, whereas
earlier work has approached the prognosis using linear
programming. The genetic programming method takes a
digitized image of a patient and automatically
generates the prediction of the time to recur as well
as the disease-free survival time. The breast cancer
dataset from the University of California Irvine
Machine Learning Repository was used for this study.
The evaluation shows that the genetic programming
approach outperforms the linear programming approach by
33 percent.",
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affiliation = "Department of Computer Science, University of
Saskatchewan, Canada",
- }
Genetic Programming entries for
Simone A Ludwig
Stefanie Roos
Citations