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[Tree-Augmented NaÏve Bayesian network model for predicting prostate cancer].
- Source :
-
Zhonghua nan ke xue = National journal of andrology [Zhonghua Nan Ke Xue] 2016 Jun; Vol. 22 (6), pp. 506-510. - Publication Year :
- 2016
-
Abstract
- Objective: To evaluate the integrated performance of age, serum PSA, and transrectal ultrasound images in the prediction of prostate cancer using a Tree-Augmented NaÏve (TAN) Bayesian network model.<br />Methods: We collected such data as age, serum PSA, transrectal ultrasound findings, and pathological diagnoses from 941 male patients who underwent prostate biopsy from January 2008 to September 2011. Using a TAN Bayesian network model, we analyzed the data for predicting prostate cancer, and compared them with the gold standards of pathological diagnosis.<br />Results: The accuracy, sensitivity, specificity, positive prediction rate, and negative prediction rate of the TAN Bayesian network model were 85.11%, 88.37%, 83.67%, 70.37%, and 94.25%, respectively.<br />Conclusions: Based on age, serum PSA, and transrectal ultrasound images, the TAN Bayesian network model has a high value for the prediction of prostate cancer, and can help improve the clinical screening and diagnosis of the disease.
Details
- Language :
- Chinese
- ISSN :
- 1009-3591
- Volume :
- 22
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Zhonghua nan ke xue = National journal of andrology
- Publication Type :
- Academic Journal
- Accession number :
- 28963838