title: Prediction of survival of ICU patients using computational intelligence.
abstract: 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 24 h 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 24 h 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.
authors: Department of Computer Science & Information Engineering, National Central University, Taiwan.
authors: Yi-Zeng
authors: YZ
authors: Hsieh
authors: Department of Computer Science & Information Engineering, National Central University, Taiwan. Electronic address: muchun@csie.ncu.edu.tw.
authors: Mu-Chun
authors: MC
authors: Su
authors: Medical Intensive Care Unit, Cathay General Hospital, Taiwan.
authors: Chen-Hsu
authors: CH
authors: Wang
authors: Quality Management Center, Cathay General Hospital, Taiwan.
authors: Pa-Chun
authors: PC
authors: Wang
mesh_terms: D000465:Algorithms; D016638:Critical Illness / Q000401:mortality*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D015233:Models, Statistical; D016571:Neural Networks, Computer
keywords: Clinical management; Computational intelligence; Fuzzy systems; ICU; Neural networks; Prediction of survival rate