DocumentCode
1800474
Title
Real-time prediction of organ failure and outcome in intensive medicine
Author
Boas, Marta Vilas ; Santos, Manuel Filpe ; Portela, Filipe ; Silva, Alvaro ; Rua, Fernando
Author_Institution
Dept. de Sist. de Informacao, Univ. do Minho, Guimaraes, Portugal
fYear
2010
fDate
16-19 June 2010
Firstpage
1
Lastpage
6
Abstract
Nowadays, there is a trend to use Data Mining models in the context of decision support for intensive medicine. Previous research has used offline data for predicting organ failure and outcome for the next day. This paper presents the INTCare system, an Intelligent Decision Support System for intensive medicine. Advances in INTCare led to a new goal, the prediction for the next hour, with real-time data, gathered in the Intensive Care Unit of Hospital Geral de Santo António, Oporto, Portugal. Interesting results were achieved, proving that it is possible to use online and real-time data to make accurate predictions for the next hour. This new approach represents an advance in intensive medicine, for hourly prediction will allow doctors to have a proactive attitude, with timely intervention, in order to avoid serious complications in the patients´ clinical condition.
Keywords
data mining; decision support systems; medical computing; INTCare system; data mining; intelligent decision support system; intensive medicine; organ failure; real-time prediction; Artificial intelligence; Cardiology; Data mining; Delta modulation; Hospitals; Monitoring; RNA; Clinical Data Mining; INTCare; Medicina Intensiva; Previsão Horária; Previsão em Tempo Real; Sistemas de Apoio à Decisão Inteligente;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Systems and Technologies (CISTI), 2010 5th Iberian Conference on
Conference_Location
Santiago de Compostela
Print_ISBN
978-1-4244-7227-7
Type
conf
Filename
5556682
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