Ali Serhan Koyuncugil

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This paper presents an application of the data mining method to determine the financial profiles of the public hospitals in Turkey. The study is based on the data compiled in 2004, covering 645 public hospitals run by the Ministry of Health (MoH) as the main provider of primary and secondary health services in Turkey. The public hospitals, currently(More)
It is very important to identify the appropriate donor in organ transplantation under the time constraint. Clearly, adequate time must be spent in appropriate donor research in that kind of vital operation. On the other hand, time is very important to search for other alternatives in case of inappropriate donor. However, the possibility for determining the(More)
The aim of this study is to develop a Financial Early Warning System (FEWS) for hospitals by using data mining. A data mining method, Chi-Square Automatic Interaction Detector (CHAID) decision tree algorithm, was used in the study for financial profiling and developing FEWS. The study was conducted in Turkish Ministry of Health’s public hospitals which were(More)
The aims of this study are to provide a standard CUR value, to determine financial and organizational factors which affect the capacity utilization and develop road maps for increasing capacity utilization. To reach these aims by an objective method, we used data mining method that discovers hidden and useful pattern in a large amount of data. Two different(More)
The aim of this study is to develop an intelligent financial early warning system model based on data mining for SMEs in Turkey. SMEs have made an important contribution to world’s rapid economic growth and the fast industrialization process. SMEs play a major role in Turkish economy and the main issue of the SMEs is finance. Therefore, developing(More)
The aim of this study is to develop road maps for financial decision making. The study was conducted in Turkish Ministry of Health’s public hospitals that need urgent solutions for financial issues in Turkey. 800 hospitals were covered and financial and operational data of the year 2005 were used in the study. We used Chi-Square Automatic(More)
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