Anal Quant Cytol Histol
February 2008
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.