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dc.contributor.authorRahman, Atiqe Ur
dc.contributor.authorSaeed, Muhammad
dc.contributor.authorMohammed, Mazin Abed
dc.contributor.authorAbdulkareem, Karrar Hameed
dc.contributor.authorNedoma, Jan
dc.contributor.authorMartinek, Radek
dc.date.accessioned2024-02-29T12:53:58Z
dc.date.available2024-02-29T12:53:58Z
dc.date.issued2023
dc.identifier.citationBiomedical Signal Processing and Control. 2023, vol. 86, art. no. 105204.cs
dc.identifier.issn1746-8094
dc.identifier.issn1746-8108
dc.identifier.urihttp://hdl.handle.net/10084/152264
dc.description.abstractSeveral 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.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesBiomedical Signal Processing and Controlcs
dc.relation.urihttps://doi.org/10.1016/j.bspc.2023.105204cs
dc.rights© 2023 Elsevier Ltd. All rights reserved.cs
dc.subjectcomplex fuzzy setcs
dc.subjectsoft setcs
dc.subjectfuzzy soft setcs
dc.subjectfuzzy parameterized fuzzy soft setcs
dc.subjecthypersoft setcs
dc.subjectliver disordercs
dc.titleAn innovative mathematical approach to the evaluation of susceptibility in liver disorder based on fuzzy parameterized complex fuzzy hypersoft setcs
dc.typearticlecs
dc.identifier.doi10.1016/j.bspc.2023.105204
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume86cs
dc.description.firstpageart. no. 105204cs
dc.identifier.wos001031709300001


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