This study introduces a new paradigm for medical diagnosis using cubic bipolar complex neutrosophic sets, suggesting improved uncertainty handling.
A new framework called Cubic Bipolar Complex Neutrosophic Sets (CBCNS) is introduced in this study to enhance how bipolar neutrosophic sets handle uncertainty. By combining the characteristics of bipolarity and cubic sets with complex neutrosophic sets, this approach allows for a more precise and flexible way of representing data. The CBCNS model builds on the existing Cubic Bipolar Neutrosophic Sets (CBNS) by adding complex-valued components. The paper formally defines the basic operations of CBCNS, along with specific distance and similarity measures designed for this structure. To demonstrate its practical value, the study includes a medical diagnosis case study, supported by a numerical example that confirms the effectiveness of the proposed method.
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V Vijaya (2025) studied this question.
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