Turkish Journal of Medical Sciences
Abstract
Serum Prostate Specific Antigen (PSA) level is used for prediction of cancer, but this approach suffers from weak sensitivity and specificity. We applied binary-split decision tree (DT) algorithm to prostate cancer prediction problem. Materials and methods: Quick, Unbiased and Efficient Statistical Tree (QUEST) algorithm was used in 750 patients who had a serum PSA levels between 0 and 10 ng/mL. Results: The analysis indicated that following five nodes had different levels of cancer possibility: (1) PSA > 5.98 ng/mL; (2) PSA 0.81; (4) PSA Keywords:
DOI
10.3906/sag-0906-47
First Page
681
Last Page
686
Recommended Citation
GÜLKESEN, K. H, KÖKSAL, İ. T, ÖZDEM, S, & SAKA, O (2010). Prediction of prostate cancer using decision tree algorithm. Turkish Journal of Medical Sciences 40 (5): 681-686. https://doi.org/10.3906/sag-0906-47
