DocumentCode :
2754241
Title :
Probabilistic fuzzy prediction of mortality in intensive care units
Author :
Fialho, A.S. ; Kaymak, U. ; Almeida, R.J. ; Cismondi, F. ; Vieira, S.M. ; Reti, S.R. ; Sousa, J.M.C. ; Finkelstein, S.N.
Author_Institution :
Eng. Syst. Div., Massachusetts Inst. of Technol., Cambridge, MA, USA
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1
Lastpage :
8
Abstract :
In the present work, we propose the application of probabilistic fuzzy systems (PFS) to model the prediction of mortality in septic shock patients. This technique is characterized by the combination of the linguistic description of the system with the statistical properties of data. Preliminary results for this particular clinical problem point that PFS models, besides performing as accurately as first order Takagi-Sugeno fuzzy models, also provide probability measures that provide additional clinical information upon which physicians can act on.
Keywords :
fuzzy set theory; hospitals; patient treatment; probability; statistics; PFS; Takagi-Sugeno fuzzy models; clinical information; clinical problem point; intensive care units; linguistic description; mortality; probabilistic fuzzy prediction; probabilistic fuzzy systems; septic shock patients; statistical properties; Electric shock; Fuzzy systems; Maximum likelihood estimation; Parameter estimation; Predictive models; Probabilistic logic; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
ISSN :
1098-7584
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2012.6251261
Filename :
6251261
Link To Document :
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