A NEW NEUTROSOPHIC ENTROPY MEASURE FORUNCERTAIN DATA IN HEALTHCARE DECISIONSUPPORT SYSTEMS

Abstract

In this paper, a novel Neutrosophic Entropy measure is proposed to effectively handle the inherent uncertainty, indeterminacy, and
inconsistency present in healthcare decision-making data. The proposed entropy measure is grounded in the principles of neutrosophic set theory and is designed to accurately evaluate the significance of decision criteria. To demonstrate the applicability and effectiveness of the proposed entropy, a Multi-Attribute Decision-Making (MADM) framework is developed for the selection of the most suitable healthcare centre. Various attributes such as service quality, cost, accessibility, medical facilities, and patient satisfaction are considered in the evaluation process. The entropy-based weighting is used to assign objective importance to each attribute, and a MADM method is employed to rank the alternatives. A case study is conducted to validate the approach, and the results highlight the robustness and practicality of the proposed method in supporting healthcare decision-making under uncertain environments.