NDLI: A survival prediction model of rats in hemorrhagic shock using the random forest classifier

Content Provider	IEEE Xplore Digital Library
Author	Joon Yul Choi Sung Kean Kim Wan Hyung Lee Tae Keun Yoo Deok Won Kim
Copyright Year	2012
Description	Author affiliation: Grad. Program in Biomed. Eng., Yonsei Univ., Seoul, South Korea (Sung Kean Kim) \|\| Brain Korea 21 Project for Med. Sci., Yonsei Univ., Seoul, South Korea (Joon Yul Choi) \|\| Dept. of Med. Eng., Yonsei Univ. Coll. of Med., Seoul, South Korea (Deok Won Kim) \|\| Yonsei Univ. Coll. of Med., Seoul, South Korea (Wan Hyung Lee; Tae Keun Yoo)
Abstract	Hemorrhagic shock is the cause of one third of deaths resulting from injury in the world. Although many studies have tried to diagnose hemorrhagic shock early and accurately, such attempts were inconclusive due to compensatory mechanisms of humans. The objective of this study was to construct a survival prediction model of rats in hemorrhagic shock using a random forest (RF) model, which is a newly emerged classifier acknowledged for its performance. Heart rate (HR), mean arterial pressure (MAP), respiratory rate (RR), lactate concentration (LC), and perfusion (PF) measured in rats were used as input variables for the RF model and its performance was compared with that of a logistic regression (LR) model. Before constructing the models, we performed a 5-fold cross validation for RF variable selection and forward stepwise variable selection for the LR model to see which variables are important for the models. For the LR model, sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (ROC-AUC) were 1, 0.89, 0.94, and 0.98, respectively. For the RF models, sensitivity, specificity, accuracy, and AUC were 0.96, 1, 0.98, and 0.99, respectively. In conclusion, the RF model was superior to the LR model for survival prediction in the rat model.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	5570
Ending Page	5573
File Size	408521
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6347256
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radio frequency Mathematical model Hemorrhaging Predictive models Input variables Electric shock Vegetation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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