Volume 21 , Issue 1 , PP: 184-191, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Neyda Hernández Bandera 1 * , Jenny Maribel M. Arizaga 2 , Enrique Rodríguez Reyes 3
Doi: https://doi.org/10.54216/IJNS.210117
Chronic obstructive pulmonary disease (COPD), is a debilitating lung condition that may lead to several other serious health problems and even death if left untreated. The ability to diagnose illnesses quickly and affordably is crucial. First and foremost, helping physicians determine how severe COPD cases are is crucial for placing patients in the appropriate institutions. Based on system engineering principles and real-world clinical practice, this article develops a COPD severity evaluation indicator system followed by suggests a neutrosophic distance from the average solution (EDAS) approach to making decisions in a linguistically uncertain setting. The alternatives are ranked by how far they are from the average answer on every factor using the EDAS technique. Distance-based multi-criteria decision-making techniques are analogous to this approach. It expedites the decision-making process by streamlining the computation of distances to an agreed solution. The EDAS method is used to compute the weights of criteria and then rank the alternatives under the neutrosophic model. The neutrosophic set is used in this paper to solve the uncertain information in the process of this evaluation. The EDAS method is applied in various criteria and alternatives and the results are discussed.
Neutrosophic Set , MCDM , EDAS , Evaluation Process , Pulmonary Disease
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