A Medical Diagnosis of Cataract Using Intuitionistic Fuzzy Sets

Abstract

Accurate decision-making in medical diagnosis investigations is complex due to the impreciseness of the patient’s symptoms in a disease that may or may not be accurate. Uncertainty is the characteristic relation between symptoms and disease. Uncertainty is best handled by linguistic variables. Intuitionistic Fuzzy Sets (IFSs) help model imprecision in decision-making problems like medical diagnosis. We propose an intuitionistic fuzzy method for the diagnosis of the cause of cataract and various factors responsible for cataract in different patients of the age group above 40 years. This model is based on the physician’s medical knowledge of the relation between the patients and of symptoms and types of cataracts using IFSs. For this purpose, we describe a state of a patient, knowing the results of his/her medical tests by the degree of membership and degree of non-membership based on the relationship between symptoms and various types of factors and types of cataracts. By the intuitionistic fuzzy max–min–max relation, we identify the disease with the maximum membership value for various patients. We illustrate the methodology with the case study of Indian patients in the Jharkhand region. The study included 50 patients over 40 years of age, of both genders, attending the general hospital for checkup or diagnosis of cataract. Causes of cataract and types of cataracts affecting the patients. Our study found that diabetes is the main cause of cataract for most patients. Patients with diabetes have posterior and cortical types of cataracts.