Cognitive Properties of MADM and Hybrid Rough Sets for Efficient Healthcare Test Diagnosis

Healthcare test diagnostic comprises the methods of finding test results in accordance with the prescribed symptoms of disease. The logic used in terms of attribute values are not sufficient to quantify the actual conditions of diagnostics, tests, or prognostics. In other words, a patient's diagnosis-test measurement is assumed to be very severe, severe, or starting to be severe. Torationalization the quantified value of severity is not always discrete. To solve this problem, we use multi attribute decision making methods to identify alternative attributes through a hybrid methodology of rough and fuzzy relations in apessimistic and optimistic parameter of covering RST in the domain of healthcare test diagnostic domain.