Tree-Augmented NaÏve Bayesian network model for predicting prostate cancer / 中华男科学杂志
National Journal of Andrology
;
(12): 506-510, 2016.
Artigo
em Chinês
| WPRIM
| ID: wpr-304710
ABSTRACT
<p><b>Objective</b>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.</p><p><b>METHODS</b>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.</p><p><b>RESULTS</b>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.</p><p><b>CONCLUSIONS</b>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.</p>
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Próstata
/
Neoplasias da Próstata
/
Biópsia
/
Sangue
/
Valor Preditivo dos Testes
/
Teorema de Bayes
/
Sensibilidade e Especificidade
/
Antígeno Prostático Específico
/
Diagnóstico
Tipo de estudo:
Estudo diagnóstico
/
Guia de Prática Clínica
/
Estudo prognóstico
Limite:
Humanos
/
Masculino
Idioma:
Chinês
Revista:
National Journal of Andrology
Ano de publicação:
2016
Tipo de documento:
Artigo
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