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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v42.i5.50
pages 45-52

Comparative Analysis of Recognition Methods of Inflammatory Processes at the Gliomas of Brain

Nina Ya. Gridina
Academician A.P. Romodanov Institute of Neurosurgery of the Academy of Medical Sciences of Ukraine, Kiev, Ukraine
Anatoliy M. Gupal
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev, Ukraine
Andrey L. Tarasov
V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine, Kiev, Ukraine

SINOPSIS

The use of Bayesian recognition procedure is described for the Markov chains and the method of k-nearest neighbors for the indices of ESR (erythrocyte sedimentation rate) at brain gliomas. The obtained results showed that the indicated methods are inferior to Bayesian recognition procedures with independent attributes.

REFERENCIAS

  1. Gupal A.M., Sergienko I.V., Optimal recognition procedures.

  2. Gridina N.Ya., Gupal A.M., Tarasov A.L., Expert system of analyzing brain gliomas progressions.

  3. Sergienko I.V., Gridina N.Ya., Gupal A.M., Tarasov A.L., The use of Bayesian recognition procedure by erythrocyte sedimentation rate when brain gliomas.

  4. Palagin A.V., Gridina N.Ya., Gupal A.M., Tarasov A.L., Computer-based system of analysis of erythrocyte sedimentation rate factors at brain gliomas.

  5. Sergienko I.V., Gridina N.Ya., Gupal A.M., Tarasov A.L., Bayesian procedure of brain gliomas recognition.

  6. Vorontsov K.V., Lectures on metrical algorithms of classification.

  7. Anderson T.W., Goodman L.A., Statistical inference about Markov chains.


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