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Understanding stroke in dialysis and chronic kidney disease

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Detalhes bibliográficos
Resumo:Patients with severe kidney failure need to be carefully monitored. One of the many treatments is called Continuous Ambulatory Peritoneal Dialysis (CAPD). This kind of treatment intends to maintain the blood tests as normal as possible. Data Mining and Machine Learning can take a simple and meaningless blood's test data set and build it into a Decision Support System. Through this article, Machine Learning algorithms will be explored with different Data Mining Models in order to extract knowledge and classify a patient with a stroke risk or not, according to their blood analysis. Peer-review under responsibility of the Conference Program Chairs.
Autores principais:Rodrigues, Mariana
Outros Autores:Peixoto, Hugo Daniel Abreu; Esteves, Marisa Araújo; Machado, José Manuel; Abelha, António
Assunto:Data Mining Classification Dialysis Stroke Risk Chronic Kidney Disease
Ano:2017
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Patients with severe kidney failure need to be carefully monitored. One of the many treatments is called Continuous Ambulatory Peritoneal Dialysis (CAPD). This kind of treatment intends to maintain the blood tests as normal as possible. Data Mining and Machine Learning can take a simple and meaningless blood's test data set and build it into a Decision Support System. Through this article, Machine Learning algorithms will be explored with different Data Mining Models in order to extract knowledge and classify a patient with a stroke risk or not, according to their blood analysis. Peer-review under responsibility of the Conference Program Chairs.