Abstract
The main aim of this study is to show how to evaluate classifications of data of Chronic Thromboembolic Pulmonary Hypertension (CTEPH) symptoms by using classical rough, classical rough nano, based covering rough and based covering rough nano topologies respectively. The attributes are examined how effective they are in detecting the disease correctly when the strong and weak, internal and external points defined in the topologies are evaluated together with the symptoms. In addition, the methods used by topologies in the detection of symptoms were explained by pseudo algorithms.