Quantifying Uncertainties Associated with Liver Disorder Using Interval-Valued Complex Fuzzy Hypersoft Set

Typically, symptoms are considered when diagnosing specific illnesses, but this does not apply to liver disorder (LDR), as it encompasses a range of symptoms that are common to various other diseases. The most effective approach is to assess a patient’s susceptibility to LDR by utilizing the features of relevant laboratory tests as metrics. This study introduces the concepts of interval-valued complex fuzzy hypersoft set (IVCFHSS), a novel mathematical framework, to aggregate and characterize patients’ susceptibility to LDR. This model is capable of addressing the combined effects of the uncertain nature of the data, sub-parametric parameter values, and periodicity. Five laboratory tests associated with LDR, are considered as parameters, and the corresponding characteristics of such laboratory tests are taken as parametric values. An easily implementable multi-attribute decision-making (MADM) scenario is employed to evaluate a proposed method for assessing patients’ susceptibility to LDR using the IVCFHSS matrix aggregations. A structural comparison of the proposed model with several pertinent, contemporary models demonstrates its flexibility and reliability.