Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/40318
Type of publication: Straipsnis Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or / and Scopus (S1)
Field of Science: Informatika / Informatics (N009)
Author(s): Martinkėnas, Arvydas;Kaminskas, Vytautas;Varoneckas, Giedrius
Title: Forecast model of impact of meteorological factors on coronary artery disease patients
Other Title: Klimato veiksnių įtakos sergantiems koronarine liga prognozavimo modelis
Is part of: Informatica : international journal. Vilnius : Institute of Mathematics and Informatics, 2007, Vol. 18, iss. 3
Extent: p. 407-418
Date: 2007
Keywords: Empirical model;Medical-meteorological weather types;Forecast of meteotropical reactions;Coronary artery disease
Abstract: Sudaryti medicininių-meteorologinių orų tipų įvertinimo ir prognozavimo empiriniai modeliai. Algoritmo ir modelio pagalba objektyvizuotas orų medicininių-meteorologinių tipų įvertinimas ir prognozavimas. Sudarytas orų medicininių-meteorologinių klasių ivertinimo bei prognozavimo empirinis modelis igalina tiksliau vertinti ir prognozuoti orus pagal jų palankumą (ar nepalankumą) sergantiems išemine širdies liga, tuo padėdamas meteoprofilaktikos vykdymui, mažinant orų itaką ligoniams, sergantiems išemine širdies liga atstatomojo gydymo etape Lietuvos pajūryje (Palanga)
A medical-meteorological weather assessment using hybrid spatial classification of synoptic and meteorological data was done. Empirical models for assessment as well as for forecast of medical-meteorological weather type at the seaside climatic zone in Palanga were developed. It was based on the data of meteofactors (atmospheric pressure, relative humidity, temperature, oxygen density in atmosphere, cyclone fronts, etc.) as well as on the occurrence of meteotropical reactions of cardiovascular function collected during 8-year period. The empirical models allow objectively assess and forecast 3 types of medical-meteorological weather types: favourable, unfavourable and very unfavourable weather. Classification model assessed favourable weather type in 56.1%, unfavourable in 31.7% and very unfavourable in 12.2%, while forecast was of favourable weather type in 52.4%, unfavourable in 46% and very unfavourable in 1.6% of days. Developed model enables more precise weather estimation and forecast meteotropical reactions promoting development of preventive measures of cardiovascular complications for reduction of negative weather impact on health in coronary artery diseases patients
Internet: http://www.mii.lt/informatica/pdf/INFO685.pdf
Affiliation(s): Informatikos fakultetas
KMU Psichofiziologijos ir reabilitacijos institutas
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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