Publicação
Information architecture for intelligent decision support in intensive medicine
| Resumo: | Daily, a great amount of data that is gathered in intensive care units, which makes intensive medicine a very attractive field for applying knowledge discovery in databases. Previously unknown knowledge can be extracted from that data in order to create prediction and decision models. The challenge is to perform those tasks in real-time, in order to assist the doctors in the decision making process. Furthermore, the models should be continuously assessed and optimized, if necessary, to maintain a certain accuracy. In this paper we propose an information architecture to support an adjustment to the INTCare system, an intelligent decision support system for intensive medicine. We focus on the automatization of data acquisition avoiding human intervention, describing its steps and some requirements. |
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| Autores principais: | Santos, Manuel |
| Outros Autores: | Portela, Filipe; Vilas Boas, Marta; Machado, José Manuel; Abelha, António; Neves, José; Silva, Álvaro; Rua, Fernando |
| Assunto: | Real-time data acquisition Knowledge discovery in databases Intensive care INTCare Intelligent decision support systems Information models |
| Ano: | 2009 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Daily, a great amount of data that is gathered in intensive care units, which makes intensive medicine a very attractive field for applying knowledge discovery in databases. Previously unknown knowledge can be extracted from that data in order to create prediction and decision models. The challenge is to perform those tasks in real-time, in order to assist the doctors in the decision making process. Furthermore, the models should be continuously assessed and optimized, if necessary, to maintain a certain accuracy. In this paper we propose an information architecture to support an adjustment to the INTCare system, an intelligent decision support system for intensive medicine. We focus on the automatization of data acquisition avoiding human intervention, describing its steps and some requirements. |
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