@InProceedings{MartinsDuPaSaFrGu:2015:MaRiEs,
author = "Martins, Fl{\'a}via de Toledo and Dutra, Luciano Vieira and
Pantale{\~a}o, Eliana and Sandri, Sandra and Freitas, Corina da
Costa and Guimar{\~a}es, Ricardo Jos{\'e} de Paula Souza e",
affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Mapeamento do risco da esquistossomose em Minas Gerais usando k-NN
e Žarvore de decis?ao",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "5912--5918",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Of all the parasitic diseases that affect humans, schistosomiasis
is one of the most widespread. Considered a serious public health
problem, the disease affects thousands of people in Brazil. Since
the implementation of schistosomiasis control program in the state
of Minas Gerais, stock control and surveillance have been
conducted. To contribute to the control and mapping of endemic
areas, the aim of this study is to obtain thematic maps showing
the risk factor for schistosomiasis mansoni in Minas Gerais.
Schistosomiasis is a disease caused by a worm that uses a snail as
intermediary host. The worm uses the water to go from the snail to
humans. Several variables can contribute for a high risk of a
population contracting the disease. In this study, this risk is
evaluated from climate, socioeconomic and remote sensing
variables, which include MODIS and SRTM data. In this work, two
pattern recognition techniques were used to generate two risk
maps, with several parameter configurations. The first one is
decision trees, for which a total of 19 classifications were
generated. The second one technique is the nearest neighbour
classification. For this method, only the number of neighbours
varied, and 11 classifications were generated. Results showed a
better result for the decistion trees in most part of the tests.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "1220",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM4EQ8",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4EQ8",
targetfile = "p1220.pdf",
type = "Sa{\'u}de",
urlaccessdate = "27 abr. 2024"
}