Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores
- Author
- Rein Houthooft (UGent) , Joeri Ruyssinck (UGent) , Joachim van der Herten (UGent) , Sean Stijven (UGent) , Ivo Couckuyt (UGent) , Bram Gadeyne (UGent) , Femke Ongenae (UGent) , Kirsten Colpaert (UGent) , Johan Decruyenaere (UGent) , Tom Dhaene (UGent) and Filip De Turck (UGent)
- Organization
- Keywords
- ICU, MULTICENTER, INTENSIVE-CARE-UNIT, Length of stay modeling, DYSFUNCTION/FAILURE, Mortality prediction, SOFA SCORE, Sequential organ failure score, Support vector machines, Critical care, IBCN, TRAUMA, REGRESSION
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-5971162
- MLA
- Houthooft, Rein, et al. “Predictive Modelling of Survival and Length of Stay in Critically Ill Patients Using Sequential Organ Failure Scores.” ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 63, no. 3, 2015, pp. 191–207, doi:10.1016/j.artmed.2014.12.009.
- APA
- Houthooft, R., Ruyssinck, J., van der Herten, J., Stijven, S., Couckuyt, I., Gadeyne, B., … De Turck, F. (2015). Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores. ARTIFICIAL INTELLIGENCE IN MEDICINE, 63(3), 191–207. https://doi.org/10.1016/j.artmed.2014.12.009
- Chicago author-date
- Houthooft, Rein, Joeri Ruyssinck, Joachim van der Herten, Sean Stijven, Ivo Couckuyt, Bram Gadeyne, Femke Ongenae, et al. 2015. “Predictive Modelling of Survival and Length of Stay in Critically Ill Patients Using Sequential Organ Failure Scores.” ARTIFICIAL INTELLIGENCE IN MEDICINE 63 (3): 191–207. https://doi.org/10.1016/j.artmed.2014.12.009.
- Chicago author-date (all authors)
- Houthooft, Rein, Joeri Ruyssinck, Joachim van der Herten, Sean Stijven, Ivo Couckuyt, Bram Gadeyne, Femke Ongenae, Kirsten Colpaert, Johan Decruyenaere, Tom Dhaene, and Filip De Turck. 2015. “Predictive Modelling of Survival and Length of Stay in Critically Ill Patients Using Sequential Organ Failure Scores.” ARTIFICIAL INTELLIGENCE IN MEDICINE 63 (3): 191–207. doi:10.1016/j.artmed.2014.12.009.
- Vancouver
- 1.Houthooft R, Ruyssinck J, van der Herten J, Stijven S, Couckuyt I, Gadeyne B, et al. Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores. ARTIFICIAL INTELLIGENCE IN MEDICINE. 2015;63(3):191–207.
- IEEE
- [1]R. Houthooft et al., “Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores,” ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 63, no. 3, pp. 191–207, 2015.
@article{5971162,
author = {{Houthooft, Rein and Ruyssinck, Joeri and van der Herten, Joachim and Stijven, Sean and Couckuyt, Ivo and Gadeyne, Bram and Ongenae, Femke and Colpaert, Kirsten and Decruyenaere, Johan and Dhaene, Tom and De Turck, Filip}},
issn = {{0933-3657}},
journal = {{ARTIFICIAL INTELLIGENCE IN MEDICINE}},
keywords = {{ICU,MULTICENTER,INTENSIVE-CARE-UNIT,Length of stay modeling,DYSFUNCTION/FAILURE,Mortality prediction,SOFA SCORE,Sequential organ failure score,Support vector machines,Critical care,IBCN,TRAUMA,REGRESSION}},
language = {{eng}},
number = {{3}},
pages = {{191--207}},
title = {{Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores}},
url = {{http://dx.doi.org/10.1016/j.artmed.2014.12.009}},
volume = {{63}},
year = {{2015}},
}
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