Markov chains pattern recognition approach applied to the medical diagnosis tasks

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Abstract

In many medical decision problems there exist dependencies between subsequent diagnosis of the same patient. Among the different concepts and methods of using "contextual" information in pattern recognition, the approach through Bayes compound decision theory is both attractive and efficient from the theoretical and practical point of view. Paper presents the probabilistic approach (based on expert rules and learning set) to the problem of recognition of state of acid-base balance and to the problem of computer-aided anti-hypertension drug therapy. The quality of obtained classifier are compared to the frquencies of correct classification of three neural nets. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Wozniak, M. (2005). Markov chains pattern recognition approach applied to the medical diagnosis tasks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3745 LNBI, pp. 231–241). https://doi.org/10.1007/11573067_24

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