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Physical Sciences and Mathematics
Florida International University
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Non-Invasive Clinical Parameters For The Prediction Of Urodynamic Bladder Outlet Obstruction: Analysis Using Causal Bayesian Networks, Myong Kim, Abhilash Cheeti, Changwon Yoo, Minsoo Choo, Jae-Seung Paick, Seung-June Oh
Non-Invasive Clinical Parameters For The Prediction Of Urodynamic Bladder Outlet Obstruction: Analysis Using Causal Bayesian Networks, Myong Kim, Abhilash Cheeti, Changwon Yoo, Minsoo Choo, Jae-Seung Paick, Seung-June Oh
School of Computing and Information Sciences
Purpose: To identify non-invasive clinical parameters to predict urodynamic bladder outlet obstruction (BOO) in patients with benign prostatic hyperplasia (BPH) using causal Bayesian networks (CBN). Subjects and Methods: From October 2004 to August 2013, 1,381 eligible BPH patients with complete data were selected for analysis. The following clinical variables were considered: age, total prostate volume (TPV), transition zone volume (TZV), prostate specific antigen (PSA), maximum flow rate (Qmax), and post-void residual volume (PVR) on uroflowmetry, and International Prostate Symptom Score (IPSS). Among these variables, the independent predictors of BOO were selected using the CBN model. The predictive performance of the …