Kemal Hakan GÜLKESEN, Sebahat ÖZDEM, Osman SAKA, İsmail Türker KÖKSAL

7186

Prediction of prostate cancer using decision tree algorithm

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
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Prediction of prostate cancer using decision tree algorithm

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
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Turkish Journal of Medical Sciences-Cover
  • ISSN: 1300-0144
  • Yayın Aralığı: 6
  • Yayıncı: TÜBİTAK
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Prediction of prostate cancer using decision tree algorithm

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