Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/17750
Título: | Grid data mining for outcome prediction in intensive care medicine |
Autor(es): | Santos, Manuel Filipe Wesley, Mathew Portela, Filipe |
Palavras-chave: | Intensive care medicine Outcome prediction Grid data mining Distributed data mining Centralized data mining |
Data: | 2011 |
Editora: | Springer |
Revista: | Communications in Computer and Information Science |
Resumo(s): | This paper introduces a distributed data mining approach suited to grid computing environments based on a supervised learning classifier system. Specific Classifier and Majority Voting methods for Distributed Data Mining (DDM) are explored and compared with the Centralized Data Mining (CDM) approach. Experimental tests were conducted considering a real world data set from the intensive care medicine in order to predict the outcome of the patients. The results demonstrate that the performance of the DDM methods are better than the CDM method. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/17750 |
ISBN: | 9783642243516 |
DOI: | 10.1007/978-3-642-24352-3_26 |
ISSN: | 1865-0929 |
Versão da editora: | http://www.springerlink.com/content/x3080p2024103014/ |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals DSI - Engenharia e Gestão de Sistemas de Informação |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Paper_1521.pdf | Documento principal | 201,68 kB | Adobe PDF | Ver/Abrir |