ТОЧНОСТЬ МЕТОДОВ СЛУЧАЙНЫЙ ЛЕС И МНОГОСЛОЙНЫЙ ПЕРСЕПТРОН В ЗАДАЧЕ ПРОГНОЗИРОВАНИЯ ИСХОДОВ ДЕТСКИХ ИШЕМИЧЕСКИХ ИНСУЛЬТОВ

Translated title of the contribution: Accuracy of Random forest method and Multilayer perceptron method in predicting of the outcomes in pediatric ischemic stroke

Research output: Contribution to journalArticle

Abstract

Authors made the comparison between two methods (random forest and multilayer perceptron) to forecast the outcome of the pediatric ischemic stroke. Two options of the outcome were estimated: disability and the absence of disability. Case series included 172 patients data base, all patients had MRI confirmation of stroke and signed concern form. Eight thrombophilic genes polymorphisms: FGB:-455G>A, F2:20210G>A, F5:1691G>A, F7:10976G>A, F13:103G>T, ITGA2:807C>T, ITGB3:1565T>C, PAI-1:-675 5G>4G, and four genes polymorphisms of folic acid enzymes: MTHFR:677C>T, MTHFR:1298А>С, МТRR:66А>G, MTR:2756А>G were established as feasible predictors. Multilayer perceptron method showed higher rates of correct recognition of the outcomes, than random forest method (0,88 vs 0,67).
Translated title of the contributionAccuracy of Random forest method and Multilayer perceptron method in predicting of the outcomes in pediatric ischemic stroke
Original languageRussian
Pages (from-to)58-62
Number of pages5
JournalУральский медицинский журнал
Issue number10(154)
Publication statusPublished - 2017

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  • 76.29.00

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