title: Belief network for grading prostate lesions.
abstract: A Bayesian belief network for grading prostatic lesions into eight primary Gleason grades was developed and tested. The network employs 13 diagnostic clues, 8 based on tissue architectural features and 5 based on nuclear features. For every diagnostic clue, three to five different outcomes are specified by membership functions. The network works in a robust fashion and attained agreement with consensus visual grading in 241 of 256 microscopic fields.
authors.affiliation: Department of Pathology and Cell Biology, Jefferson Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania 19107-5244.
authors.forename: M
authors.initials: M
authors.lastname: Bibbo
authors.forename: P H
authors.initials: PH
authors.lastname: Bartels
authors.forename: T
authors.initials: T
authors.lastname: Pfeifer
authors.forename: D
authors.initials: D
authors.lastname: Thompson
authors.forename: C
authors.initials: C
authors.lastname: Minimo
authors.forename: H G
authors.initials: HG
authors.lastname: Davidson
mesh_terms: D000230:Adenocarcinoma / Q000473:pathology* / Q000648:ultrastructure; D001499:Bayes Theorem; D002467:Cell Nucleus / Q000473:pathology; D003937:Diagnosis, Differential; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000648:ultrastructure