Bayesian belief network for the Gleason patterns in prostatic adenocarcinoma: development of a diagnostic decision support system for educational purposes.

Objective: To develop a Bayesian belief network (BBN) for Gleason grading of prostate adenocarcinoma.

Study Design: A shallow network was developed for Gleason grading with open-tree topology, with a root node containing 5 subjective diagnostic alternatives and 8 first-level descendant nodes for diagnostic features. Features or diagnostic clues of the descendant nodes were based on architecture of Gleason patterns.