Medical Diagnosis by Roughness-Cosine Similarity Measure in Rough Neutrosophic Set Environment

Abstract

Diagnosing the types of disease before treatment starts is the most important task for medical staff. Usually, a patient’s disease is investigated based on the symptoms that exist such as temperature records for viral fever and stomach pain for malaria. Therefore, in this research, relationships between patients’ records and symptoms and disease and symptoms were analyzed using the roughness-Cosine similarity measure. For a more presentable result, the rough neutrosophic set was used in the development of the proposition for the roughness-Cosine similarity measure. All the data collected were also represented in a rough neutrosophic set environment where lower and upper approximations exist. The comparative result indicates that all the patients were suffering from viral fever.