Prediction of prostate cancer using decision tree algorithm

Authors

KEMAL HAKAN GÜLKESEN
İSMAİL TÜRKER KÖKSAL
SEBAHAT ÖZDEM
OSMAN SAKA

DOI

10.3906/sag-0906-47

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:

First Page

681

Last Page

686

Recommended Citation

GÜLKESEN, KEMAL HAKAN; KÖKSAL, İSMAİL TÜRKER; ÖZDEM, SEBAHAT; and SAKA, OSMAN (2010) "Prediction of prostate cancer using decision tree algorithm," Turkish Journal of Medical Sciences: Vol. 40: No. 5, Article 2. https://doi.org/10.3906/sag-0906-47
Available at: https://journals.tubitak.gov.tr/medical/vol40/iss5/2