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Machine Learning Applications for Classification Emergency and Non-Emergency Patients

Machine Learning Applications for Classification Emergency and Non-Emergency Patients

Zeynel Abidin Çil, Abdullah Caliskan
Copyright: © 2020 |Pages: 17
ISBN13: 9781799825814|ISBN10: 1799825817|EISBN13: 9781799825821
DOI: 10.4018/978-1-7998-2581-4.ch006
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MLA

Çil, Zeynel Abidin, and Abdullah Caliskan. "Machine Learning Applications for Classification Emergency and Non-Emergency Patients." Computational Intelligence and Soft Computing Applications in Healthcare Management Science, edited by Muhammet Gul, et al., IGI Global, 2020, pp. 104-120. https://doi.org/10.4018/978-1-7998-2581-4.ch006

APA

Çil, Z. A. & Caliskan, A. (2020). Machine Learning Applications for Classification Emergency and Non-Emergency Patients. In M. Gul, E. Celik, S. Mete, & F. Serin (Eds.), Computational Intelligence and Soft Computing Applications in Healthcare Management Science (pp. 104-120). IGI Global. https://doi.org/10.4018/978-1-7998-2581-4.ch006

Chicago

Çil, Zeynel Abidin, and Abdullah Caliskan. "Machine Learning Applications for Classification Emergency and Non-Emergency Patients." In Computational Intelligence and Soft Computing Applications in Healthcare Management Science, edited by Muhammet Gul, et al., 104-120. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2581-4.ch006

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Abstract

Emergency departments of hospitals are busy. In recent years, patient arrivals have significantly risen at emergency departments in Turkey like other countries in the world. The main important features of emergency services are uninterrupted service, providing services in a short time, and priority to emergency patients. However, patients who do not need immediate treatment can sometimes apply to this department due to several reasons like working time and short waiting time. This situation can reduce efficiency and effectiveness at emergency departments. On the other hand, computers solve complex classification problems by using machine learning methods. The methods have a wide range of applications, such as computational biology and computer vision. Therefore, classification of emergency and non-emergency patients is vital to increase productivity of the department. This chapter tries to find the best classifier for detection of emergency patients by utilizing a data set.

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