Applying Data Mining for Prostate Cancer

Facing the phenomenon of "ageing population", the diagnosis and treatment of prostate cancer has become a serious menpsilas health issue in Taiwan. This study aimed to provide new scientific and quantitative information for traditional Chinese medicine (TCM) physicians in clinical practice of prostate cancer. In this study, data mining techniques were employed to explore the hidden knowledge among meridian energy of prostate cancer from 213 patientspsila health examination data including patient demographics and evaluations for the prostate-specific antigen (PSA) blood test as well as the meridian energy. Through the construction of decision tree, totally ten classification rules for predicting prostate cancer are extracted. The average correction classification accuracy is close to 80%. The findings are considered as helpful reference in diagnosis and treatment of prostate cancer for TCM physicians.