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Real-Time Decision Support Using Data Mining to Predict Blood Pressure Critical Events in Intensive Medicine Patients

  • Filipe PortelaEmail author
  • Manuel Filipe Santos
  • José Machado
  • António Abelha
  • Fernando Rua
  • Álvaro Silva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9456)

Abstract

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95 %.

Keywords

Data mining Intcare Intensive medicine Blood pressure Critical events Decision support Real-Time 

Notes

Acknowledgments

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013 and the contract PTDC/EEI-SII/1302/2012 (INTCare II).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Filipe Portela
    • 1
    • 3
    Email author
  • Manuel Filipe Santos
    • 1
  • José Machado
    • 1
  • António Abelha
    • 1
  • Fernando Rua
    • 2
  • Álvaro Silva
    • 2
  1. 1.Algoritmi CentreUniversity of MinhoBragaPortugal
  2. 2.Serviço Cuidados IntensivosCentro Hospitalar do Porto, Hospital Santo AntónioPortoPortugal
  3. 3.ESEIGPorto PolytechnicPortoPortugal

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