Cartesian Genetic Programming and its Application to Medical Diagnosis
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- @Article{Smith:2012:ieeeCIM,
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author = "Stephen L. Smith",
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title = "Cartesian Genetic Programming and its Application to
Medical Diagnosis",
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journal = "IEEE Computational Intelligence Magazine",
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year = "2011",
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month = nov,
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volume = "6",
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number = "4",
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pages = "56--67",
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size = "12 pages",
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abstract = "Cartesian Genetic Programming (CGP) is a form of
genetic programming that is flexible and adaptable to a
range of problems. In this article, a particular
representation of CGP, known as implicit context
representation CGP is presented and its application to
two medical conditions: the diagnosis of Parkinson'
disease and the detection of breast cancer from
mammograms. CGP has a number of advantages over
conventional genetic programming and is well suited to
the highly non-linear problems considered here. Summary
results are presented for the application of CGP to
real patient data that are sufficiently encouraging to
warrant further clinical trials which are currently in
progress.",
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keywords = "genetic algorithms, genetic programming, cartesian
genetic programming, CGP, Parkinson disease, breast
cancer detection, context representation, mammograms,
medical diagnosis application, diseases, mammography,
medical computing, patient diagnosis",
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DOI = "doi:10.1109/MCI.2011.942583",
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ISSN = "1556-603X",
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notes = "Also known as \cite{6052376}",
- }
Genetic Programming entries for
Stephen L Smith
Citations