Mehmet Kayaalp, M.D., M.S., Gregory F. Cooper, M.D., Ph.D., Gilles...  Home/Search
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Abstract: Objective: This study evaluates the effectiveness of the stationarity assumption in predicting the mortality of intensive care unit (ICU) patients at the ICU discharge. Design: This is a comparative study. A stationary temporal Bayesian network learned from data was compared to a set of (33) nonstationary temporal Bayesian networks learned from data. A process observed as a sequence of events is stationary if its stochastic properties stay the same when the sequence is shifted in a positive or... (Update)
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BibTeX entry: (Update)
M. Kayaalp, G. Cooper and G. Clermont, Predicting ICU mortality: A comparison of stationary and nonstationary temporal models. in: J. Overhage, ed, Converging Information, Technology, and Health Care, proceedings of AMIA Symposium (AMIA, Los Angeles CA, USA, 2000) 418--422. http://citeseer.ist.psu.edu/kayaalp00predicting.html More
@inproceedings{ kayaalp2000amia,
author = "Mehmet Kayaalp and Gregory F. Cooper and Gilles Clermont",
title = "Predicting ICU Mortality: A Comparison of Stationary and Nonstationary Temporal Models",
booktitle = "Proc AMIA Symp.",
pages = "418–422",
year = "2000",
url = "citeseer.ist.psu.edu/kayaalp00predicting.html" }
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