Title :
Data Mining a Prostate Cancer Dataset Using Neural Networks
Author_Institution :
Sch. of Comput. Sci., Univ. of Westminster, London
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;
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
DOI :
10.1109/NEUREL.2006.341201
