An innovative mathematical approach to the evaluation of susceptibility in liver disorder based on fuzzy parameterized complex fuzzy hypersoft set

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10252759" target="_blank" >RIV/61989100:27240/23:10252759 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1746809423006377" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1746809423006377</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.bspc.2023.105204" target="_blank" >10.1016/j.bspc.2023.105204</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An innovative mathematical approach to the evaluation of susceptibility in liver disorder based on fuzzy parameterized complex fuzzy hypersoft set

Popis výsledku v původním jazyce

Several liver diseases are collectively termed as liver disorder. Usually the diagnosis of a particular disease is accomplished by considering symptoms as parameters but this is not the case for liver disorder due to the involvement of large number of symptoms relating to several diseases. The most suitable approach is to assess the susceptibility of patients for liver disorder by considering the features of relevant laboratory tests as parameters. In this study the characterization and aggregations of novel mathematical model fuzzy parameterized complex fuzzy hypersoft set (FpcFHSS) are utilized to evaluate the susceptibility of patients for liver disorder. This model is capable to cope with uncertain nature of parameters, the classification of parameters into their respective sub-parametric values and the periodicity of data collectively. The five appropriate laboratory test features relevant to liver disorder are considered as parameters and their standard ranges are opted as sub-parametric values. The uncertain nature of sub-parametric tuples is managed by assigning them a fuzzy parameterized degree which is determined with the suitable criteria. Using the matrix aggregations of FpcFHSS, an algorithm is proposed for the assessment of the susceptibility of patients for liver disorder and then validated with the help of real-world multi-attribute decision-making application. The reliability and flexibility of proposed model are discussed by its structural comparison with some pre-developed relevant models. (C) 2023 Elsevier Ltd

Název v anglickém jazyce

An innovative mathematical approach to the evaluation of susceptibility in liver disorder based on fuzzy parameterized complex fuzzy hypersoft set

Popis výsledku anglicky

Several liver diseases are collectively termed as liver disorder. Usually the diagnosis of a particular disease is accomplished by considering symptoms as parameters but this is not the case for liver disorder due to the involvement of large number of symptoms relating to several diseases. The most suitable approach is to assess the susceptibility of patients for liver disorder by considering the features of relevant laboratory tests as parameters. In this study the characterization and aggregations of novel mathematical model fuzzy parameterized complex fuzzy hypersoft set (FpcFHSS) are utilized to evaluate the susceptibility of patients for liver disorder. This model is capable to cope with uncertain nature of parameters, the classification of parameters into their respective sub-parametric values and the periodicity of data collectively. The five appropriate laboratory test features relevant to liver disorder are considered as parameters and their standard ranges are opted as sub-parametric values. The uncertain nature of sub-parametric tuples is managed by assigning them a fuzzy parameterized degree which is determined with the suitable criteria. Using the matrix aggregations of FpcFHSS, an algorithm is proposed for the assessment of the susceptibility of patients for liver disorder and then validated with the help of real-world multi-attribute decision-making application. The reliability and flexibility of proposed model are discussed by its structural comparison with some pre-developed relevant models. (C) 2023 Elsevier Ltd

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Biomedical Signal Processing and Control

ISSN

1746-8094

e-ISSN

—

Svazek periodika

86

Číslo periodika v rámci svazku

SEP 2023

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

11

Strana od-do

—

Kód UT WoS článku

001031709300001

EID výsledku v databázi Scopus

2-s2.0-85164034960