NDLI: Hopfield neural network and fuzzy Hopfield neural network for diagnosis of liver disorders

Content Provider	IEEE Xplore Digital Library
Author	Neshat, M. Zadeh, A.E.
Copyright Year	2010
Description	Author affiliation: Department of Computer Engineering, University Islamic, Azad of shirvan branch, Iran (Neshat, M.) \|\| Department of medical science University Mashhad Iran, Iran (Zadeh, A.E.)
Abstract	nowadays, artificial intelligence has a wide usage especially for designing intelligent systems in medicine. Diagnosing and determining different kinds of diseases are a part of this system's duties. In this research tried to diagnose liver disorders more accurate by using Hopfield neural network and fuzzy Hopfield beside fuzzy C-Means. Requiring data including 345 records and 6 fields is chosen from valid data bank (UCI) there are 6 inputs and the rate of network liver disorders risk is the output. In comparison with traditional diagnoses this system is faster, more economical, more reliable and more accurate. In the best state of training, Hopfield neural network and fuzzy Hopfield neural network diagnose liver disorders with the accuracy of 88.2% and 92% respectively. These results have been examined and proved experimentally under observation of specialists. Regarding diverse neural networks which been applied in diagnosing liver disorders, results have been an agreeable improvement.
Starting Page	162
Ending Page	167
File Size	122484
Page Count	6
File Format	PDF
ISBN	9781424451630
DOI	10.1109/IS.2010.5548321
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hopfield neural networks Fuzzy neural networks Medical diagnostic imaging Artificial intelligence Biomedical imaging Artificial neural networks Medical diagnosis Liver diseases Neural networks Biochemistry liver disorders neural network fuzzy Hopfield
Content Type	Text
Resource Type	Article

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