Decision making in medical diagnosis by using single-valued neutrosophic sets / Nur Hasnani Mohd Rodzi, Nur Solehah Mohammad Zuki and Nor Siti Hajar Zukifli

Medical diagnosis contains uncertain, incomplete, inconsistent information and these information described the relationship between symptoms and diseases. Medical experts take a long time to gain accurate final diagnosis results since they need to deal with uncertain, incomplete and inconsistent information. Intuitionistic Fuzzy set contains questionable results that may lead to false diagnosis of patients’ symptom. Thus, this research is conducted to compute Single Valued Neutrosophic sets (SVNs) for patient’s symptoms and diagnosis of disease, compare the results of distance and similarity measures in the medical diagnosis environment and choose the best diagnosis result for patient suffering disease based on distance and similarity measures. Two formulas of distance measure used are normalized Hamming and Euclidean distance. Eight different formula of similarity measure are also used in this research. Final result after applying all methods, we found that P1 suffering from malaria, P2 suffering from stomach problem, P3 suffering from typhoid and P4 suffering from viral fever.