Data Mining a Prostate Cancer Dataset Using Neural Networks

Author

Revett, Kenneth

Author_Institution

Sch. of Comput. Sci., Univ. of Westminster, London

fYear

2006

fDate

25-27 Sept. 2006

Firstpage

157

Lastpage

160

Abstract

Prostate cancer remains one of the leading causes of cancer death worldwide, with a reported incidence rate of 650,000 cases per annum worldwide. The causal factors of prostate cancer still remain to be determined. In this paper, we investigate a medical dataset containing clinical information on 502 prostate cancer patients using the machine learning technique of rough sets and radial basis function neural network. Our preliminary results yield a classification accuracy of 90%, with high sensitivity and specificity (both at approximately 91%). Our results yield a predictive positive value (PPN) of 81% and a predictive negative value (PNV) of 95%

Keywords

cancer; data mining; decision tables; learning (artificial intelligence); medical computing; radial basis function networks; rough set theory; clinical information; data mining; machine learning technique; neural network; predictive negative value; predictive positive value; prostate cancer dataset; radial basis function neural network; rough set; Cancer detection; Data mining; Machine learning; Medical diagnostic imaging; Neural networks; Prostate cancer; Radial basis function networks; Rough sets; Seminars; Testing; Rough sets; cancer classifier; machine learning; prostate cancer dataset; reducts;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on

Conference_Location

Belgrade, Serbia & Montenegro

Print_ISBN

1-4244-0433-9

Electronic_ISBN

1-4244-0433-9

Type

conf

DOI

10.1109/NEUREL.2006.341201

Filename

4147189