title: Clinical applications of Bayesian belief networks in pathology.
abstract: Bayesian belief networks (BBNs) are a novel tool for representing knowledge about diagnostic decision making and for obtaining a numerical measure of certainty in the final diagnosis. Belief networks have been applied to the pathological assessment of breast, prostate and skin lesions and have been shown to provide consistency in the grading of microscopic features and improve diagnosis. These applications are reviewed in the current paper. The application of BBNs has been further facilitated through the use of standardised imagery which is stored digitally and used to enter evidence into a BBN. It is predicted that the further development of BBNs with improved logical capabilities represent the key to improved decision making in pathology.
authors.affiliation: Department of Pathology, Queen's University of Belfast, Northern Ireland, UK.
authors.forename: P W
authors.initials: PW
authors.lastname: Hamilton
authors.forename: R
authors.initials: R
authors.lastname: Montironi
authors.forename: W
authors.initials: W
authors.lastname: Abmayr
authors.forename: M
authors.initials: M
authors.lastname: Bibbo
authors.forename: N
authors.initials: N
authors.lastname: Anderson
authors.forename: D
authors.initials: D
authors.lastname: Thompson
authors.forename: P H
authors.initials: PH
authors.lastname: Bartels
mesh_terms: D001499:Bayes Theorem; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D019044:Image Cytometry; D008297:Male; D016571:Neural Networks, Computer; D010338:Pathology, Clinical / Q000379:methods*