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THE RELATIONSHIP OF THE INTERNATIONAL PROSTATE SYMPTOM SCORE AND OBJECTIVE PARAMETERS FOR DIAGNOSING BLADDER OUTLET OBSTRUCTION. PART II: THE POTENTIAL USEFULNESS OF ARTIFICIAL NEURAL NETWORKS

Authors
Journal
The Journal of Urology
0022-5347
Publisher
Elsevier
Publication Date
Volume
165
Issue
1
Identifiers
DOI: 10.1097/00005392-200101000-00009
Keywords
  • Bladder
  • Computer Simulation
  • Urination Disorders
  • Neural Networks (Computer)
  • Bladder Neck Obstruction
Disciplines
  • Computer Science
  • Medicine

Abstract

Purpose The International Prostate Symptom Score (I-PSS) is used exclusively for evaluating patients with a prostate condition and following various treatment modalities. As previously demonstrated, there is poor or no correlation of bladder outlet obstruction diagnosed by pressure flow study with the symptoms projected by the I-PSS. Thus, we applied an artificial neural network model to assess patients with lower urinary tract symptoms. Materials and Methods Data on 460 patients enrolled in part 1 of our study were entered into a multilayer feed forward, back propagation network. Results In the training set of 305 patients the model predicted obstruction in 94% with 94% sensitivity and 68% specificity. In the test set of 155 patients it predicted obstruction in 87% with 87% sensitivity and 44% specificity. Conclusions The accuracy of the model for diagnosing obstruction based on the I-PSS is acceptable, considering that statistical models failed to demonstrate a correlation of symptoms with objective obstruction.

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