Significance of Fuzzy Logic in the Medical Science

Kaur, Jagmohan; Khehra, Baljit Singh; Singh, Amarinder

doi:10.1007/978-981-16-8225-4_38

Cited by 4 publications

(4 citation statements)

References 27 publications

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“…Fuzzy theory and fuzzy systems have made significant progress in many applications since their inception. Fuzzy logic is becoming an extremely suitable and satisfactory tool for the development of real-time applicable expert systems in the medical science; see, for example, a paper presenting the diversity of works on fuzzy logic to identify the risk of various diseases and also revealing a model for the direct service of patients from old age homes to intensive care units (ICU) through ambulance services [6]. A fuzzy logic-based optimal network system for the delivery of medical goods via drones and land transport in remote areas is presented in [7].…”

Section: Introductionmentioning

confidence: 99%

Generalized Type 2 Fuzzy Differential Evolution Applied to a Sugeno Controller

Ochoa

Peraza

Castillo

et al. 2023

Axioms

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The papers using fuzzy logic have generated continuous improvements for applications, and an example of this is the use of generalized type 2 fuzzy systems in real-world problems. The key idea of this paper is to present a generalized type 2 fuzzy system for augmenting differential evolution with dynamic parameter variation in order to enhance its performance and convergence. A generalized type 2 Sugeno controller was implemented with the aim of enhancing the trajectory of a robot, and an analysis of the execution time and the errors obtained by ITAE, IAE, ITSE, ISEV, RMSE, and MSE is presented. In addition, a comparison with different levels of disturbance applied to the controller was performed with the goal of demonstrating the efficiency of a type 2 fuzzy system.

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Section: Introductionmentioning

confidence: 99%

Generalized Type 2 Fuzzy Differential Evolution Applied to a Sugeno Controller

Ochoa

Peraza

Castillo

et al. 2023

Axioms

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“…Fuzzy logic has a significant role in medical science due to its complexity. Applications like cardiology, endocrinology, urology, ophthalmology, and dentistry are some of the numerous medical fields in which fuzzy logic is applied [3]. Also, the concept of fuzzy logic deals with problems including pattern recognition, medical diagnosis, and decision-making [4].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

“…Also, the concept of fuzzy logic deals with problems including pattern recognition, medical diagnosis, and decision-making [4]. Thus, the ambition of using fuzzy logic in medicine is to generate results like an expert and diagnose the patients at an early stage [3]. Nevertheless, the theory of Zadeh about fuzzy sets is limited in the sense that it is defined by membership grade only [4].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Intelligent Medical Diagnosis Reasoning Using Composite Fuzzy Relation, Aggregation Operators and Similarity Measure of q-Rung Orthopair Fuzzy Sets

Dounis,

Stefopoulos

2023

Applied Sciences

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Medical diagnosis is the process of finding out what is the disease a person may be suffering from. From the symptoms and their gradation, the doctor can decide which the dominant disease is. Nevertheless, in the process of medical diagnosis, there is ambiguity, uncertainty, and a lack of medical knowledge that can adversely affect the doctor’s judgment. Thus, a tool of artificial intelligence, fuzzy logic, has come to enhance the decision-making of diagnosis in a medical environment. Fuzzy set theory uses the membership degree to characterize the uncertainty and, therefore, fuzzy sets are integrated into imperfect data in order to make a reliable diagnosis. The patient’s medical status is represented as q-rung orthopair fuzzy values. In this paper, many versions and methodologies were applied such as the composite fuzzy relation, fuzzy sets extensions (q-ROFS) with aggregation operators, and similarity measures, which were proposed as decision-making intelligent methods. The aim of this procedure was to find out which of the diseases (viral fever, malaria fever, typhoid fever, stomach problems, and chest problems), was the most influential for each patient. The work emphasizes the contribution of aggregation operators in medical data in order to contain more than one expert’s aspect. The performance of the methodology was quite good and interesting as most of the results were in agreement with previous works.

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“…Work striving for better controllers has developed an idea called fuzzy logic. Although it was created as early as the 1960s [1], its practical application development has occurred only recently [2,3]. The use of fuzzy controllers is becoming popular, due to the ease of implementation and the good quality of regulation [4].…”

Section: Introductionmentioning

confidence: 99%

Implementation of Type-2 Fuzzy Controller in Matlab Software

Dominik,

Flaga

2023

Adv. Sci. Technol. Res. J.

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The purpose of this work is to create a Matlab toolbox that makes it easy and accessible to become acquainted with a novel control method called type-2 fuzzy controller. A toolbox for working with type-1 controllers can be found in the Simulink package, while there are only few, simple toolboxes for type-2 fuzzy controllers. The article describes the details of the created software, which allows working both with simulation objects, but also enables creating program code for a PLC industrial controller. This gives the opportunity to work in a simulation environment with a model of the control object and then, after tuning the controller, to automatically implement the controller to control the real object. In the literature, one can find many methods for reducing type-2 to type-1 fuzzy logic, but most often they are compared to several well-known classical reduction methods, such as the KM algorithm. There is no compilation of the most popular methods and a comparison of their performance. With the new toolbox it was possible to quickly create and add new reduction methods; thus, an analysis of 16 reduction methods was also presented in the article.

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Significance of Fuzzy Logic in the Medical Science

Cited by 4 publications

References 27 publications

Generalized Type 2 Fuzzy Differential Evolution Applied to a Sugeno Controller

Generalized Type 2 Fuzzy Differential Evolution Applied to a Sugeno Controller

Intelligent Medical Diagnosis Reasoning Using Composite Fuzzy Relation, Aggregation Operators and Similarity Measure of q-Rung Orthopair Fuzzy Sets

Implementation of Type-2 Fuzzy Controller in Matlab Software

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