• 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