Heptapartitioned Neutrosophic Soft Matrices and its Application in Medical Diagnosis

In real-life situations, we often encounter challenges involving uncertainty, vague ness, complexity, and unpredictability. Heptapartitioned Neutrosophic Sets serve as a mathe matical tool to address issues that existing methods cannot effectively resolve. Heptapartitioned Neutrosophic Soft Matrices play a vital role in managing indeterminate and inconsistent infor mation during the decision-making process. This paper focuses on exploring the concepts of Heptapartitioned Neutrosophic Sets, Heptapartitioned Neutrosophic Soft Sets, and Heptaparti tioned Neutrosophic Soft Matrices, which are highly effective in handling situations involving uncertainty and imprecision. It further proposes a novel method for constructing decision ma trices using these soft matrices as a practical application of the theory. The study introduces an algorithm based on Heptapartitioned Neutrosophic Soft Matrices to address problems in disease diagnosis by analyzing patient symptoms. Specifically, it examines the relationship between patients and symptoms, as well as between symptoms and diseases, using these ma trices. To support decision-making, a score matrix is defined by applying max-min operations and complementation of Heptapartitioned Neutrosophic Soft Matrices.