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Genomics and Applied Biology
2014, Vol.5, No.3
http://gab.sophiapublisher.com
their own in detecting abnormalities, at least they can
help physician in selecting suspicious situations or in
deciding his resultant decision.
In our study, we classified prostate cancer data of 50
subjects by AIS and ANN. By taking the clonal
selection model in immune system, a code for AIS
was written and applied to the dataset for
classification. With best system parameters, AIS has
reached a test classification ratio of 93.33% by
misclassifying only 1 test data. On the other hand
ANN has reached 100% accuracy. Whereas it is not
possible to do a confidential comparison between AIS
and ANN methods for 50 data, we can say that ANN
can be searched for more crowded datasets for a
real-life application to help doctors.
Acknowledgement
This work is supported by the Coordinatorship of Selçuk
University's Scientific Research Projects Grant.
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