Literature DB >> 1558613

Expert systems in histopathology. IV. The management of uncertainty.

P H Bartels1, D Thompson, J E Weber.   

Abstract

Expert systems deal with data that are categorical and conceptual, that represent elements of fuzzy sets and that often, by themselves, do not allow an unequivocal decision. The management of uncertainty in expert systems thus becomes a crucial issue. It involves defining measures of uncertainty and procedures for combining accumulating evidence in a manner that properly considers the dependence structure of diagnostic clues. Probability theory offers valuable procedures for uncertainty assessment; however, their practical application in the domain of quantitative histopathology and histopathologic diagnosis can be problematic.

Mesh:

Year:  1992        PMID: 1558613

Source DB:  PubMed          Journal:  Anal Quant Cytol Histol        ISSN: 0884-6812            Impact factor:   0.302


  5 in total

1.  How to develop and use a Bayesian Belief Network.

Authors:  R Montironi; W F Whimster; Y Collan; P W Hamilton; D Thompson; P H Bartels
Journal:  J Clin Pathol       Date:  1996-03       Impact factor: 3.411

Review 2.  Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.

Authors:  R A Miller
Journal:  J Am Med Inform Assoc       Date:  1994 Jan-Feb       Impact factor: 4.497

3.  Expert system support using Bayesian belief networks in the diagnosis of fine needle aspiration biopsy specimens of the breast.

Authors:  P W Hamilton; N Anderson; P H Bartels; D Thompson
Journal:  J Clin Pathol       Date:  1994-04       Impact factor: 3.411

4.  Diagnostic distance of high grade prostatic intraepithelial neoplasia from normal prostate and adenocarcinoma.

Authors:  R Montironi; R Pomante; P Colanzi; D Thompson; P W Hamilton; P H Bartels
Journal:  J Clin Pathol       Date:  1997-09       Impact factor: 3.411

5.  The development of a decision support system for the pathological diagnosis of human cerebral tumours based on a neural network classifier.

Authors:  G Sieben; M Praet; H Roels; G Otte; L Boullart; L Calliauw
Journal:  Acta Neurochir (Wien)       Date:  1994       Impact factor: 2.216

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.