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dc.contributor.authorCherkashina, Yuliya Andreevnaen
dc.contributor.authorGerget, Olga Mikhailovnaen
dc.date.accessioned2016-11-24T10:06:39Z-
dc.date.available2016-11-24T10:06:39Z-
dc.date.issued2016-
dc.identifier.citationCherkashina Yu. A. Regression analysis for solving diagnosis problem of children's health / Yu. A. Cherkashina, O. M. Gerget // IOP Conference Series: Materials Science and Engineering. — 2016. — Vol. 124 : Mechanical Engineering, Automation and Control Systems (MEACS2015) : International Conference, 1–4 December 2015, Tomsk, Russia : [proceedings]. — [012047, 6 p.].ru
dc.identifier.urihttp://earchive.tpu.ru/handle/11683/33847-
dc.description.abstractThe paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.en
dc.language.isoenen
dc.publisherIOP Publishingru
dc.relation.ispartofIOP Conference Series: Materials Science and Engineering. Vol. 124 : Mechanical Engineering, Automation and Control Systems (MEACS2015). — Bristol, 2016.ru
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.subjectрегрессивный анализru
dc.subjectдиагностикаru
dc.subjectздоровьеru
dc.subjectдетиru
dc.subjectнеонатальный периодru
dc.subjectлогическая регрессияru
dc.subjectуравнения регрессииru
dc.titleRegression analysis for solving diagnosis problem of children's healthen
dc.typeConference Paperen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.typeinfo:eu-repo/semantics/conferencePaperen
dcterms.audienceResearchesen
local.departmentНациональный исследовательский Томский политехнический университет (ТПУ)::Институт кибернетики (ИК)::Кафедра прикладной математики (ПМ)ru
local.description.firstpage12047-
local.filepathhttp://dx.doi.org/10.1088/1757-899X/124/1/012047-
local.identifier.bibrecRU\TPU\network\13690-
local.identifier.colkeyRU\TPU\col\18700-
local.identifier.perskeyRU\TPU\pers\36279-
local.identifier.perskeyRU\TPU\pers\31430-
local.localtypeДокладru
local.volume124-
local.conference.nameMechanical Engineering, Automation and Control Systems (MEACS2015)-
local.conference.date2015-
dc.identifier.doi10.1088/1757-899X/124/1/012047-
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