Publicação
Real-time intelligent decision support and monitoring system of critical patients
| Resumo: | Intensive care units are places where patients’ vital signs are continuously monitored and recorded alongside a multiplicity of clinical parameters. The main goal of this work is to study and develop an intelligent system to promote new decision-making knowledge crucial to provide better treatment to the patient. This article presents the achieved goals; in particular, the system developed for monitoring the clinical data and, using data mining technologies, for predicting clinical events with great sensitivity (90–100%), including organ failure probability, read-missions, and sepsis. |
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| Autores principais: | Portela, Filipe |
| Outros Autores: | Dos Santos, Manuel Filipe Vieira Torres; Abelha, António; Machado, José Manuel; Silva, Álvaro Moreira; Martins, Fernando Rua |
| Assunto: | Data mining Intelligent decision support system Intensive medicine Real-time online learning |
| Ano: | 2017 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Intensive care units are places where patients’ vital signs are continuously monitored and recorded alongside a multiplicity of clinical parameters. The main goal of this work is to study and develop an intelligent system to promote new decision-making knowledge crucial to provide better treatment to the patient. This article presents the achieved goals; in particular, the system developed for monitoring the clinical data and, using data mining technologies, for predicting clinical events with great sensitivity (90–100%), including organ failure probability, read-missions, and sepsis. |
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