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A fuzzy inference system for prevent...

Beechner, Paul Martin.

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A fuzzy inference system for preventing ambulance diversion in emergency departments.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	A fuzzy inference system for preventing ambulance diversion in emergency departments./
作者:	Beechner, Paul Martin.
面頁冊數:	145 p.
附註:	Source: Masters Abstracts International, Volume: 52-02.
Contained By:	Masters Abstracts International52-02(E).
標題:	Engineering, Industrial. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1543602
ISBN:	9781303309748

A fuzzy inference system for preventing ambulance diversion in emergency departments.
Beechner, Paul Martin.

A fuzzy inference system for preventing ambulance diversion in emergency departments. - 145 p.

Source: Masters Abstracts International, Volume: 52-02.

Thesis (M.S.)--State University of New York at Binghamton, 2013.

The hospital emergency department (ED) is an extremely important area of the hospital and serves a diverse patient population. The population that utilizes the ED is of varying acuity levels, varying illnesses, different demographics, and different ages. The objective of this research is to construct a fuzzy inference system that performs as a decision support system to eliminate ambulance diversion in the ED. This system takes information or input factors from the ED and recommends a certain percentage of lower acuity patients to divert from the ED to outpatient clinics or primary care physicians. The systems were validated against the baseline values for need for diversion and the error was calculated. The queue network performed much better than the simulation model fuzzy inference system when MSE was compared. The error for the queue network FIS was relatively low and it performed well across most of the data range.

ISBN: 9781303309748Subjects--Topical Terms:

626639
Engineering, Industrial.

A fuzzy inference system for preventing ambulance diversion in emergency departments.
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520 $a The hospital emergency department (ED) is an extremely important area of the hospital and serves a diverse patient population. The population that utilizes the ED is of varying acuity levels, varying illnesses, different demographics, and different ages. The objective of this research is to construct a fuzzy inference system that performs as a decision support system to eliminate ambulance diversion in the ED. This system takes information or input factors from the ED and recommends a certain percentage of lower acuity patients to divert from the ED to outpatient clinics or primary care physicians. The systems were validated against the baseline values for need for diversion and the error was calculated. The queue network performed much better than the simulation model fuzzy inference system when MSE was compared. The error for the queue network FIS was relatively low and it performed well across most of the data range.
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