ANT_FDCSM: A novel fuzzy rule miner derived from ant colony meta-heuristic for diagnosis of diabetic patients
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Title
ANT_FDCSM: A novel fuzzy rule miner derived from ant colony meta-heuristic for diagnosis of diabetic patients
Authors
Keywords
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Journal
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Volume -, Issue -, Pages 1-14
Publisher
IOS Press
Online
2018-08-15
DOI
10.3233/jifs-172240
References
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Related references
Note: Only part of the references are listed.- Machine Learning and Data Mining Methods in Diabetes Research
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- (2013) Fayssal Beloufa et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
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- (2011) Mohamed Amine Chikh et al. JOURNAL OF MEDICAL SYSTEMS
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- (2010) B. Chandra et al. PATTERN RECOGNITION
- The Economic Costs of Undiagnosed Diabetes
- (2009) Yiduo Zhang et al. Population Health Management
- A cascade learning system for classification of diabetes disease: Generalized Discriminant Analysis and Least Square Support Vector Machine
- (2006) Kemal Polat et al. EXPERT SYSTEMS WITH APPLICATIONS
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