Inference Algorithms for Systems of Medical Diagnosis Aid based on Bayesian Networks
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Abstract
Several scientific works have modeled medical problems with assistance of Bayesian networks, assisting doctors in the task of diagnosing a disease given the observed symptoms and evaluated exams. This paper aims to present the execution time and convergence analyses for exact and approximate algorithms for probabilistic inference, which allow to apply the Bayesian reasoning in the support to the medical diagnosis. The results of the analyses supply a criterion for the choice of the algorithm to be implemented depending on the resources that are wished to optimize.
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How to Cite
Sampaio, R. M., Valentim, F. L., de Souza, L. A., & Silva, R. M. de A. (2008). Inference Algorithms for Systems of Medical Diagnosis Aid based on Bayesian Networks. INFOCOMP Journal of Computer Science, 7(2), 84–89. Retrieved from https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/222
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