Uncertainty in Artificial Intelligence
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A Heuristic Bayesian Approach to Knowledge Acquisition: Application to the Analysis of Tissue-Type Plasminogen Activator
Ross Shachter, David Eddy, Vic Hasselblad, Robert Wolpert
Abstract:
This paper describes a heuristic Bayesian method for computing probability distributions from experimental data, based upon the multivariate normal form of the influence diagram. An example illustrates its use in medical technology assessment. This approach facilitates the integration of results from different studies, and permits a medical expert to make proper assessments without considerable statistical training.
Keywords: Heuristic Bayesian Method, Probability Distributions, Influence Diagram, Medical
Pages: 183-190
PS Link:
PDF Link: /papers/87/p183-shachter.pdf
BibTex:
@INPROCEEDINGS{Shachter87,
AUTHOR = "Ross Shachter and David Eddy and Vic Hasselblad and Robert Wolpert",
TITLE = "A Heuristic Bayesian Approach to Knowledge Acquisition: Application to the Analysis of Tissue-Type Plasminogen Activator",
BOOKTITLE = "Uncertainty in Artificial Intelligence 3 Annual Conference on Uncertainty in Artificial Intelligence (UAI-87)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1987",
PAGES = "183--190"
}


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