caa a22 4500 60616054X CHVBK 20210128100630.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00521-014-1631-z doi (NATIONALLICENCE)springer-10.1007/s00521-014-1631-z Patient admission prediction using a pruned fuzzy min-max neural network with rule extraction [Elektronische Daten] [Jin Wang, Chee Lim, Douglas Creighton, Abbas Khorsavi, Saeid Nahavandi, Julien Ugon, Peter Vamplew, Andrew Stranieri, Laura Martin, Anton Freischmidt] A useful patient admission prediction model that helps the emergency department of a hospital admit patients efficiently is of great importance. It not only improves the care quality provided by the emergency department but also reduces waiting time of patients. This paper proposes an automatic prediction method for patient admission based on a fuzzy min-max neural network (FMM) with rules extraction. The FMM neural network forms a set of hyperboxes by learning through data samples, and the learned knowledge is used for prediction. In addition to providing predictions, decision rules are extracted from the FMM hyperboxes to provide an explanation for each prediction. In order to simplify the structure of FMM and the decision rules, an optimization method that simultaneously maximizes prediction accuracy and minimizes the number of FMM hyperboxes is proposed. Specifically, a genetic algorithm is formulated to find the optimal configuration of the decision rules. The experimental results using a large data set consisting of 450740 real patient records reveal that the proposed method achieves comparable or even better prediction accuracy than state-of-the-art classifiers with the additional ability to extract a set of explanatory rules to justify its predictions. Springer-Verlag London, 2014 Patient admission prediction nationallicence Fuzzy min-max neural network nationallicence Genetic algorithm nationallicence Rule extraction nationallicence Wang Jin Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut Lim Chee Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut Creighton Douglas Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut Khorsavi Abbas Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut Nahavandi Saeid Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut Ugon Julien School of Science, Information Technology and Engineering, Federation University, 3350, Ballarat, VIC, Australia aut Vamplew Peter School of Science, Information Technology and Engineering, Federation University, 3350, Ballarat, VIC, Australia aut Stranieri Andrew School of Science, Information Technology and Engineering, Federation University, 3350, Ballarat, VIC, Australia aut Martin Laura Redesign and Innovation Unit, Ballarat Health Services, 3350, Ballarat, VIC, Australia aut Freischmidt Anton Department of Health, Commission for Hospital Improvement, Ballarat, VIC, Australia aut Neural Computing and Applications Springer London 26/2(2015-02-01), 277-289 0941-0643 26:2<277 2015 26 521 https://doi.org/10.1007/s00521-014-1631-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1631-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Jin Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut NATIONALLICENCE 700 1- Lim Chee Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut NATIONALLICENCE 700 1- Creighton Douglas Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut NATIONALLICENCE 700 1- Khorsavi Abbas Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut NATIONALLICENCE 700 1- Nahavandi Saeid Center for Intelligent Systems Research, Deakin University, 3217, Waurn Ponds, VIC, Australia aut NATIONALLICENCE 700 1- Ugon Julien School of Science, Information Technology and Engineering, Federation University, 3350, Ballarat, VIC, Australia aut NATIONALLICENCE 700 1- Vamplew Peter School of Science, Information Technology and Engineering, Federation University, 3350, Ballarat, VIC, Australia aut NATIONALLICENCE 700 1- Stranieri Andrew School of Science, Information Technology and Engineering, Federation University, 3350, Ballarat, VIC, Australia aut NATIONALLICENCE 700 1- Martin Laura Redesign and Innovation Unit, Ballarat Health Services, 3350, Ballarat, VIC, Australia aut NATIONALLICENCE 700 1- Freischmidt Anton Department of Health, Commission for Hospital Improvement, Ballarat, VIC, Australia aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/2(2015-02-01), 277-289 0941-0643 26:2<277 2015 26 521