Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7081
Title: Modified Mixture of Experts for Diabetes Diagnosis
Authors: Übeyli, Elif Derya
Keywords: Automated diagnostic systems
Decision support system
Modified mixture of experts
Diabetes diagnosis
Issue Date: 2009
Publisher: Springer
Abstract: Diagnosis tasks are among the most interesting activities in which to implement intelligent systems. The major objective of the paper is to be a guide for the readers, who want to develop an automated decision support system for detection of diabetics and subjects having risk factors of diabetes. The purpose was to determine an optimum classification scheme with high diagnostic accuracy for this problem. Several different classification algorithms were tested and their performances in detection of diabetics were compared. The performance of the classification algorithms was illustrated on the Pima Indians diabetes data set. The present research demonstrated that the modified mixture of experts (MME) achieved diagnostic accuracies which were higher than that of the other automated diagnostic systems.
URI: https://doi.org/10.1007/s10916-008-9191-3
https://hdl.handle.net/20.500.11851/7081
ISSN: 0148-5598
1573-689X
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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