Prediction of survival of ICU patients using computational intelligence

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107149

Title:	Prediction of survival of ICU patients using computational intelligence
Authors:	蘇木春;Hsieh, Yi-Zeng;Su, Mu-Chun;Wang, Chen-Hsu;Wang, Pa-Chun
Contributors:	資訊電機學院資訊工程學系
Keywords:	Algorithms;Clinical management;Computational intelligence;Critical Illness - mortality;Diagnosis, Computer-Assisted - methods;Fuzzy Logic;Fuzzy systems;Hospitals;Humans;ICU;Intensive Care Units - statistics & numerical data;Internal Medicine;Models, Statistical;Mortality;Neural networks;Neural Networks (Computer);Other;Patients;Prediction of survival rate
Date:	2014-04-01
Issue Date:	2026-04-23 13:58:04 (UTC+8)
Publisher:	Elsevier Ltd.;United States: Elsevier Ltd
Abstract:	摘要： This paper presents a computational-intelligence-based model to predict the survival rate of critically ill patients who were admitted to an intensive care unit (ICU). The prediction input variables were based on the first 24h admission physiological data of ICU patients to forecast whether the final outcome was survival or not. The prediction model was based on a particle swarm optimization (PSO)-based Fuzzy Hyper-Rectangular Composite Neural Network (PFHRCNN) that integrates three computational intelligence tools including hyper-rectangular composite neural networks, fuzzy systems and PSO. It could help doctors to make appropriate treatment decisions without excessive laboratory tests. The performance of the proposed prediction model was evaluated on the data set collected from 300 ICU patients in the Cathy General Hospital in 2012. There were 10 input variables in total for the prediction model. Nine of these variables (e.g. systolic arterial blood pressures, systolic non-invasive blood pressures, respiratory rate, heart rate, and body temperature) were routinely available for 24h in ICU and the last variable is patient's age. The proposed model could achieve a 96% and 86% accuracy rate for the training data and testing data, respectively. 其他題名： Comput Biol Med 出版者： United States: Elsevier Ltd 出版日期： 2014-04-01 出處： Computers in biology and medicine, 2014-04, Vol.47, p.13-19 版權： 2014 Elsevier Ltd 版權： Elsevier Ltd 版權： Copyright © 2014 Elsevier Ltd. All rights reserved. 版權： Copyright Elsevier Limited Apr 2014 識別號： ISSN: 0010-4825 識別號： ISSN: 1879-0534 識別號： EISSN: 1879-0534 識別號： DOI: 10.1016/j.compbiomed.2013.12.012 識別號： PMID: 24508564 識別號： CODEN: CBMDAW
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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