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Knowledge discovery from surgical waiting lists

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Detalhes bibliográficos
Resumo:Methods for knowledge discovery in data bases (KDD) have been studied for more than a decade. New methods are required owing to the size and complexity of data collections in administration, business and science. They include procedures for data query and extraction, for data cleaning, data analysis, and methods of knowledge representation. The part of KDD dealing with the analysis of the data has been termed data mining. Data mining is the process of pattern discovery and extraction where huge amount of data is involved. Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. In this work is presented an approach for the use of data mining in the context of waiting lists for surgery, namely for predicting the type of surgery (programmed or additional) for a record in the list.
Autores principais:Neto, Cristiana
Outros Autores:Peixoto, Hugo Daniel Abreu; Abelha, Vasco António Pinheiro Costa; Abelha, António; Machado, José Manuel
Assunto:Knowledge Discovery in Databases Data mining Surgery waiting list Decision Support Systems Classification
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:Methods for knowledge discovery in data bases (KDD) have been studied for more than a decade. New methods are required owing to the size and complexity of data collections in administration, business and science. They include procedures for data query and extraction, for data cleaning, data analysis, and methods of knowledge representation. The part of KDD dealing with the analysis of the data has been termed data mining. Data mining is the process of pattern discovery and extraction where huge amount of data is involved. Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. In this work is presented an approach for the use of data mining in the context of waiting lists for surgery, namely for predicting the type of surgery (programmed or additional) for a record in the list.