Risk Stratification with Extreme Learning Machine: A Retrospective Study on Emergency Department Patients

This paper presents a novel risk stratification method using extreme learning machine (ELM). ELM was integrated into a scoring system to identify the risk of cardiac arrest in emergency department (ED) patients. The experiments were conducted on a cohort of 1025 critically ill patients presented to the ED of a tertiary hospital. ELM and voting based ELM (V-ELM) were evaluated. To enhance the prediction performance, we proposed a selective V-ELM (SV-ELM) algorithm. The results showed that ELM based scoring methods outperformed support vector machine (SVM) based scoring method in the receiver operation characteristic analysis.

[1]  Kwangsoo Shin,et al.  Robust algorithm for arrhythmia classification in ECG using extreme learning machine , 2009, Biomedical engineering online.

[2]  Jacek M. Zurada,et al.  Review and performance comparison of SVM- and ELM-based classifiers , 2014, Neurocomputing.

[3]  Han Wang,et al.  Evolutionary Extreme Learning Machine and Its Application to Image Analysis , 2013, J. Signal Process. Syst..

[4]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[5]  Narasimhan Sundararajan,et al.  Classification of Mental Tasks from Eeg Signals Using Extreme Learning Machine , 2006, Int. J. Neural Syst..

[6]  C. Subbe,et al.  Effect of introducing the Modified Early Warning score on clinical outcomes, cardio‐pulmonary arrests and intensive care utilisation in acute medical admissions * , 2003, Anaesthesia.

[7]  D. Serre.  Matrices: Theory and Applications , 2002 .

[8]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[9]  E. Antman,et al.  The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. , 2000, JAMA.

[10]  Hongming Zhou,et al.  Extreme Learning Machine for Regression and Multiclass Classification , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[11]  Shifei Ding,et al.  Extreme learning machine and its applications , 2013, Neural Computing and Applications.

[12]  Chee Kheong Siew,et al.  Extreme learning machine: Theory and applications , 2006, Neurocomputing.

[13]  Dianhui Wang,et al.  Extreme learning machines: a survey , 2011, Int. J. Mach. Learn. Cybern..

[14]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[15]  Qiuqi Ruan,et al.  Cross-Modality 2D-3D Face Recognition via Multiview Smooth Discriminant Analysis Based on ELM , 2014, J. Electr. Comput. Eng..

[16]  R. Suganya,et al.  Data Mining Concepts and Techniques , 2010 .

[17]  J. Crowcroft,et al.  Automatic epileptic seizure detection in EEGs based on optimized sample entropy and extreme learning machine , 2012, Journal of Neuroscience Methods.

[18]  Xizhao Wang,et al.  Dynamic ensemble extreme learning machine based on sample entropy , 2012, Soft Comput..

[19]  Zhan-Li Sun,et al.  A Neuro-Fuzzy Inference System Through Integration of Fuzzy Logic and Extreme Learning Machines , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[20]  Amaury Lendasse,et al.  OP-ELM: Optimally Pruned Extreme Learning Machine , 2010, IEEE Transactions on Neural Networks.

[21]  P. Saratchandran,et al.  Multicategory Classification Using An Extreme Learning Machine for Microarray Gene Expression Cancer Diagnosis , 2007, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[22]  Nan Liu,et al.  Voting based extreme learning machine , 2012, Inf. Sci..

[23]  Han Wang,et al.  Ensemble Based Extreme Learning Machine , 2010, IEEE Signal Processing Letters.

[24]  Jiuwen Cao,et al.  Protein Sequence Classification with Improved Extreme Learning Machine Algorithms , 2014, BioMed research international.

[25]  Nan Liu,et al.  Patient Outcome Prediction with Heart Rate Variability and Vital Signs , 2011, J. Signal Process. Syst..

[26]  A. Kai Qin,et al.  Evolutionary extreme learning machine , 2005, Pattern Recognit..

[27]  R. Venkatesh Babu,et al.  No-reference image quality assessment using modified extreme learning machine classifier , 2009, Appl. Soft Comput..

[28]  Nan Liu,et al.  An Intelligent Scoring System and Its Application to Cardiac Arrest Prediction , 2012, IEEE Transactions on Information Technology in Biomedicine.