Correlation and Regression Coefficients of Neutrosophic Graph Products using Minimum Spanning Tree for Enhancing Healthcare Strategies

Abstract

This paper investigates the correlation and regression coefficients (CRCs) of single-valued neutro
sophic graph products (SVNGPs) with a focus on the minimum spanning tree (MST) and their applications
 in enhancing healthcare strategies. Single-valued neutrosophic Graph (SVNG) is an extension of traditional
 graph theory that uses neutrosophic logic to solve uncertainties and indeterminacy. We have introduced the
 modular and strong products of SVNGs and calculated the CRCs with and without using MST to evaluate the
 relationships within healthcare networks. A comparative analysis has been done for CRCs with and without
 MST which helps to increase the accuracy and efficiency of CRCs. The gained results offer valuable insights
 into optimizing resource allocation and improving patient care by identifying critical factors influencing health
care outcomes. This study demonstrates the applicability of SVNGPs in decision-making processes, with MST
 playing a pivotal role in enhancing overall healthcare efficiency and effectiveness

DOI: 10.5281/zenodo.14232707