|Paper title:||Evolutionary Forecasting Method of Treatment Results|
|Published in:||Issue 2, (Vol. 7) / 2013Download|
|Abstract.||Processing method of poorly formalized multivariable arrays of biomedical information, based on evolutional method for solving of extreme tasks of multivariable function, is presented in the article. Method allows predicting treatment results take account of biomedical and social features of the patients. Method allows selecting the weights of input parameters without preliminary reduction of the multidimensional feature space which eliminates the loss of important information and to identify weak links in these information arrays. Results of numerical experiments which have shown high efficiency of method are presented. Value of the mean average prognostication error amounted to 10-17%. Developed method can be used in various subject areas in which information about the objects kept in the large volume data sets, are described in the protocols of "input-output", and for them the hypothesis of monotony of the decision- making in the local area is valid.|
|Keywords:||Data Processing, Evolutionary Method, Biomedical Information, Forecasting, Program Complex, Support Decision Making|
1. Z.Michalewicz Genetic algorithms + data structures = evolution programs. Berlin etc.: Springer, 1996.
2. A.A.Freitas Data Mining and Knowledge Discovery with Evolutionary Algorithms. Berlin etc.: Springer, 2002.
3. I.H.Witten, E.Frank, M.A.Hall Data mining: Practical machine learning, tools and techniques. Elsevier, 2011.
4. I.A.Tsygankova “Program complex system of decision-making,” Software & Systems. Moscow, pp. 155-158, N 4, 2008 in Russian with English abstract.
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