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Journal of Healthcare Engineering
Volume 2016, Article ID 7035463, 11 pages
Research Article

Length of Hospital Stay Prediction at the Admission Stage for Cardiology Patients Using Artificial Neural Network

1Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan
2Division of Health Insurance, Mackay Memorial Hospital, Taipei 10449, Taiwan
3Medical Affairs Department, Mackay Memorial Hospital, Taipei 10449, Taiwan
4Registration and Admitting, Mackay Memorial Hospital, Taipei 10449, Taiwan

Received 1 September 2015; Revised 21 February 2016; Accepted 15 March 2016

Academic Editor: Hélder A. Santos

Copyright © 2016 Pei-Fang (Jennifer) Tsai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

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  • Joeri Ruyssinck, Joachim van der Herten, Rein Houthooft, Femke Ongenae, Ivo Couckuyt, Bram Gadeyne, Kirsten Colpaert, Johan Decruyenaere, Filip De Turck, and Tom Dhaene, “Random Survival Forests for Predicting the Bed Occupancy in the Intensive Care Unit,” Computational and Mathematical Methods in Medicine, vol. 2016, pp. 1–7, 2016. View at Publisher · View at Google Scholar
  • X. Zhang, J. Kim, R. E. Patzer, S. R. Pitts, A. Patzer, and J. D. Schrager, “Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks*,” Methods of Information in Medicine, vol. 56, no. 5, 2017. View at Publisher · View at Google Scholar
  • Azadeh Oliyaei, and Zahra Aghababaee, “Prediction Length of Stay with Neural Network Trained by Particle Swarm Optimization,” International Journal of Big Data and Analytics in Healthcare, vol. 2, no. 2, pp. 21–38, 2017. View at Publisher · View at Google Scholar