Mediative Sugeno’s-TSK Fuzzy Logic Based Screening Analysis to Diagnosis of Heart Disease

Dhiman, Nitesh; Sharma, Manoj

doi:10.4236/am.2019.106032

Cited by 10 publications

(5 citation statements)

References 16 publications

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“…To solve this new difficulty, integrative models such as “fuzzy logic” may be a useful mathematical tool for handling various types of uncertainties as in the case of these new virus strains. The fuzzy logic framework can be used in different types of disease diagnosis, mainly chronic non-communicable, but few infections in which the knowledge of the doctors and experts is represented on behalf of the symptoms and diseases [ 28 ]. In addition, fuzzy logic has been used for the increase, optimization, and preparation of hospitals placed in low- and medium-resource countries facing natural disasters, or as in the present case, with COVID-19 [ 18 ].…”

Section: Applications Of Different Fuzzy Techniques On First Covid-19 Wave In Hospital Emergenciesmentioning

confidence: 99%

Performance of Fuzzy Multi-Criteria Decision Analysis of Emergency System in COVID-19 Pandemic. An Extensive Narrative Review

Clemente-Suárez

Navarro-Jiménez

Ruisoto

et al. 2021

IJERPH

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The actual coronavirus disease 2019 (COVID-19) pandemic has led to the limit of emergency systems worldwide, leading to the collapse of health systems, police, first responders, as well as other areas. Various ways of dealing with this world crisis have been proposed from many aspects, with fuzzy multi-criteria decision analysis being a method that can be applied to a wide range of emergency systems and professional groups, aiming to confront several associated issues and challenges. The purpose of this critical review was to discuss the basic principles, present current applications during the first pandemic wave, and propose future implications of this methodology. For this purpose, both primary sources, such as scientific articles, and secondary ones, such as bibliographic indexes, web pages, and databases, were used. The main search engines were PubMed, SciELO, and Google Scholar. The method was a systematic literature review of the available literature regarding the performance of the fuzzy multi-criteria decision analysis of emergency systems in the COVID-19 pandemic. The results of this study highlight the importance of the fuzzy multi-criteria decision analysis method as a beneficial tool for healthcare workers and first responders’ emergency professionals to face this pandemic as well as to manage the created uncertainty and its related risks.

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Section: Applications Of Different Fuzzy Techniques On First Covid-19 Wave In Hospital Emergenciesmentioning

confidence: 99%

Performance of Fuzzy Multi-Criteria Decision Analysis of Emergency System in COVID-19 Pandemic. An Extensive Narrative Review

Clemente-Suárez

Navarro-Jiménez

Ruisoto

et al. 2021

IJERPH

View full text Add to dashboard Cite

show abstract

“…This initial proposal was only for type-1 fuzzy logic and was viewed as an extension of intuitionistic fuzzy logic. Later, other authors have applied this concept to several medical problems, such as heart disease diagnosis [5,6], diabetes diagnosis [7], prediction of the COVID-19 pandemic [8] and others [9]. In summary, most of the existing works utilizing MFL have been carried out in relation to the medical diagnosis area, where the knowledge of several medical experts is combined to improve the diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Proposal for Mediative Fuzzy Control: From Type-1 to Type-3

Castillo,

Melin

2023

Symmetry

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This paper presents an initial proposal for the utilization of mediative fuzzy logic in control problems. Mediative fuzzy logic (MFL) was originally proposed with the idea of modeling situations in which there exists contradictory knowledge among several experts in an application domain. In this situation, a mediative solution may be a better choice in this particular decision-making situation. In this paper, we are extending the concept of fuzzy control to the realm of MFL for situations in which we have two or more control experts, and the design of the fuzzy controller has to be based on their knowledge. In this situation, we are taking advantage of the symmetrical nature of membership functions in reducing the complexity of designing the fuzzy controllers. The goal of this study was to improve control results by combining the knowledge of several experts, which MFL is aimed at executing. The initial architecture of mediative fuzzy control for type-1 fuzzy logic is presented, and an illustrative example is used to better comprehend the proposed approach. Later, we extend type-1 MFL to the realms of type-2 and type-3 fuzzy logic, and we also provide a comparative study that exhibits that the type-3 version surpasses the type-2 and type-1 versions of mediative fuzzy control. The idea of utilizing type-2 and type-3 is to improve the capabilities of the fuzzy controller in handling uncertainty coming from noise in the control process.

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“…Montiel et al [3] gave a new method that can handle contrary information and provided a logical solution known as the meditative solution.Mediative fuzzy logic is a novel approach for the management of contradictory knowledge by generalizing the concept of an intuitionistic fuzzy set [4] . The concept of mediative fuzzy logic has widely been used in disease diagnosis [5] ; Multi-Criteria Decision Support System [6] ; in COVID-19 pandemic [7] and many more. Almost every content of the mathematical problems involves imprecision.…”

Section: Introductionmentioning

confidence: 99%