Type-2 Fuzzy Neural System for Diagnosis of Diabetes

Diabetes is a chronic disease that is characterized by insufficient production or utilization of insulin and a consequent high increase in blood sugar. Diagnosis of diabetes is a complex process and requires a high level of expertise. The disease is characterized by a set of signs and symptoms. Some...

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Autores principales:	Rahib H. Abiyev, Hamit Altiparmak
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/f7ace19218914f86bd9bb4591ba6c4ed
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spelling	oai:doaj.org-article:f7ace19218914f86bd9bb4591ba6c4ed2021-11-29T00:55:39ZType-2 Fuzzy Neural System for Diagnosis of Diabetes1563-514710.1155/2021/5854966https://doaj.org/article/f7ace19218914f86bd9bb4591ba6c4ed2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/5854966https://doaj.org/toc/1563-5147Diabetes is a chronic disease that is characterized by insufficient production or utilization of insulin and a consequent high increase in blood sugar. Diagnosis of diabetes is a complex process and requires a high level of expertise. The disease is characterized by a set of signs and symptoms. Some of these symptoms are obtained through laboratory analysis. Creation of a knowledge base and automation of disease diagnosis are important and allow fast detection and treatment. Various techniques have been used to develop a high-accuracy system for the diagnosis of diabetes. Fuzzy logic is one of the appropriate methodologies for the development of such medical diagnostic systems. Several research studies have used fuzzy models to diagnose medical diseases due to the imprecision and uncertainty associated with medical data. Moreover, a high level of uncertainty in medical data requires a type-2 fuzzy system to handle these uncertainties and diagnose diabetes. The paper proposes the integration of a type-2 fuzzy system and neural networks for the diagnosis of diabetes. Using the structure of type-2 fuzzy neural network (T2FNN) and statistical data, the system’s design for the diagnosis of diabetes is performed. A number of simulations have been done in order to evaluate the performance of the designed system. The comparative results demonstrated the efficiency of using the T2FNN system in the diagnosis of diabetes. The physician can use the system for diabetes’ diagnosis.Rahib H. AbiyevHamit AltiparmakHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Rahib H. Abiyev Hamit Altiparmak Type-2 Fuzzy Neural System for Diagnosis of Diabetes
description	Diabetes is a chronic disease that is characterized by insufficient production or utilization of insulin and a consequent high increase in blood sugar. Diagnosis of diabetes is a complex process and requires a high level of expertise. The disease is characterized by a set of signs and symptoms. Some of these symptoms are obtained through laboratory analysis. Creation of a knowledge base and automation of disease diagnosis are important and allow fast detection and treatment. Various techniques have been used to develop a high-accuracy system for the diagnosis of diabetes. Fuzzy logic is one of the appropriate methodologies for the development of such medical diagnostic systems. Several research studies have used fuzzy models to diagnose medical diseases due to the imprecision and uncertainty associated with medical data. Moreover, a high level of uncertainty in medical data requires a type-2 fuzzy system to handle these uncertainties and diagnose diabetes. The paper proposes the integration of a type-2 fuzzy system and neural networks for the diagnosis of diabetes. Using the structure of type-2 fuzzy neural network (T2FNN) and statistical data, the system’s design for the diagnosis of diabetes is performed. A number of simulations have been done in order to evaluate the performance of the designed system. The comparative results demonstrated the efficiency of using the T2FNN system in the diagnosis of diabetes. The physician can use the system for diabetes’ diagnosis.
format	article
author	Rahib H. Abiyev Hamit Altiparmak
author_facet	Rahib H. Abiyev Hamit Altiparmak
author_sort	Rahib H. Abiyev
title	Type-2 Fuzzy Neural System for Diagnosis of Diabetes
title_short	Type-2 Fuzzy Neural System for Diagnosis of Diabetes
title_full	Type-2 Fuzzy Neural System for Diagnosis of Diabetes
title_fullStr	Type-2 Fuzzy Neural System for Diagnosis of Diabetes
title_full_unstemmed	Type-2 Fuzzy Neural System for Diagnosis of Diabetes
title_sort	type-2 fuzzy neural system for diagnosis of diabetes
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/f7ace19218914f86bd9bb4591ba6c4ed
work_keys_str_mv	AT rahibhabiyev type2fuzzyneuralsystemfordiagnosisofdiabetes AT hamitaltiparmak type2fuzzyneuralsystemfordiagnosisofdiabetes
_version_	1718407809861681152

Type-2 Fuzzy Neural System for Diagnosis of Diabetes

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