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Reduced-rule based expert system by the simplification of logic functions for the diagnosis of diabetes

Computers in Biology and Medicine · Haziran 2011

Özet
Diabetes is a chronic and complex endocrine disease with metabolic disorders caused by the imbalance between secreted and needed insulin levels. In the present study, all probabilities were examined considering ten (10) indications (210=1024 different cases) of diabetes using medical expert system (MES), and accordingly, a truth table was established. This table was simplified by the simplification method of logic functions. 15 main rules were obtained using minimization method for Boolean Functions (BFs). These rules established rules base of ES. Subsequently, the parameters of 768 patients were compared with this ES. Accuracy rate of the estimations of MES, created as a result these comparisons, was determined as 97.13% in diabetes patients, 97% in non-diabetes patients, 96.5% in Type 1 patients, 98.26% in Type 2 patients and 97.44% in pregnant patients. © 2011 Elsevier Ltd.
12 atıf Haziran 2011 DOI
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YÖKSİS Kayıtları
Reduced rule based expert system by the simplification of logic functions for the diagnosis of diabetes
Computers in Biology and Medicine · 2011 SCI
Prof. Dr. FATİH BAŞÇİFTÇİ →
Reduced rule based expert system by the simplification of logic functions for the diagnosis of diabetes
Computers in Biology and Medicine · 2011 SCI
Prof. Dr. FATİH BAŞÇİFTÇİ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Bu dergide (ISSN eşleşmesi) kurumun 3 kaydı bulundu.
Pairwise FCM based feature weighting for improved classification of vertebral column disorders
2014 ISSN: 0010-4825 SCI-Expanded
Prof. Dr. HASAN ERDİNÇ KOÇER →
Reduced rule based expert system by the simplification of logic functions for the diagnosis of diabetes
2011 ISSN: 00104825 SCI
Prof. Dr. FATİH BAŞÇİFTÇİ →
Gray level co occurrence and random forest algorithm based genderdetermination with maxillary tooth plaster images
2016 ISSN: 0010-4825 SCI-Expanded Q2
Doç. Dr. HATİCE KÖK →

Makale Bilgileri

Toplam Atıf 12 atıf · Scopus
ISSN00104825
Yayın TarihiHaziran 2011
Cilt / Sayfa41 · 350-356

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey

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Scimago Dergi (ISSN Eşleşmesi)
Computers in Biology and Medicine
Q1
SJR Skoru1,375
H-Index164
YayıncıElsevier Ltd
ÜlkeUnited Kingdom
Computer Science Applications (Q1)
Health Informatics (Q1)
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12
Atıf

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