Predicting Length of Stay in Intensive Care Units after Cardiac Surgery: Comparison of Artificial Neural Networks and Adaptive Neuro-fuzzy System-Reference-Cited by-同舟云学术

Predicting Length of Stay in Intensive Care Units after Cardiac Surgery: Comparison of Artificial Neural Networks and Adaptive Neuro-fuzzy System

Published:2018 Issue:2 Volume:24 Page:109
ISSN:2093-3681
Container-title:Healthcare Informatics Research
language:en
Short-container-title:Healthc Inform Res

Author:

Maharlou Hamidreza¹²,Niakan Kalhori Sharareh R.³,Shahbazi Shahrbanoo⁴,Ravangard Ramin¹⁵

Affiliation:

1. Department of Health Services Management, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.

2. Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.

3. Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

4. Shiraz Anesthesiology and Critical Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.

5. Health Human Resources Research Centre, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.

Publisher

The Korean Society of Medical Informatics

Subject

Health Information Management,Health Informatics,Biomedical Engineering

Link

https://synapse.koreamed.org/pdf/10.4258/hir.2018.24.2.109

Reference38 articles.

1. University of California San Francisco. ICU outcome [Internet]. San Francisco (CA). University of California. c2018. cited at 2018 Apr 1. Available from: https://healthpolicy.ucsf.edu/icu-outcomes

2. Comparison of Regression Methods for Modeling Intensive Care Length of Stay

3. Length of intensive care unit stay following cardiac surgery: is it impossible to find a universal prediction model?

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