Constructing Bayesian Networks for Medical Diagnosis from Incomplete and Partially Correct Statistics

  title={Constructing Bayesian Networks for Medical Diagnosis from Incomplete and Partially Correct Statistics},
  author={Daniel Nikovski},
  journal={IEEE Trans. Knowl. Data Eng.},
The paper discusses several knowledge engineering techniques for the construction of Bayesian networks for medical diagnostics when the available numerical probabilistic information is incomplete or partially correct. This situation occurs often when epidemiological studies publish only indirect statistics and when signi cant unmodeled conditional dependence exists in the problem domain. While nothing can replace precise and complete probabilistic information, still a useful diagnostic system… CONTINUE READING
Highly Cited
This paper has 460 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 90 extracted citations

461 Citations

Citations per Year
Semantic Scholar estimates that this publication has 461 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 15 references

On the impact of causal independence

  • I. Rish, R. Dechter
  • Stanford Spring Symposium on Interactive and…
  • 1998

Clustered knowledge representation: Increasing the reliability of computerized expert systems

  • H. Yu, P. J. Haug, M. J. Lincoln, C. W. Turner, H. R. Warner
  • In Proceedings of the Twelfth Symposium for…
  • 1988

Similar Papers

Loading similar papers…