امین محمدی

  In this research, the design of a decision support system for the management of the Covid-۱۹ disease has been introduced. Since this virus has a high transmission speed and the longer the virus spreads, the more mutated it becomes, so there is a need to quickly identify sick people. Because with the quick identification of sick people, the treatment process can be started faster, and it is also possible to apply quarantine to the relatives of the sick person to prevent the transmission of this virus as much as possible. In this thesis, a system has been designed and implemented to manage the demands of patients and doctors as well as the maximum allocation of resources to accelerate the treatment process, control and prevent the spread of the disease. In this system, the allocated resources include medical centers (whether clinics or hospitals) as well as doctors or nurses in medical centers and hospitals. These resources are used for the process of treating patients with covid-۱۹ and the possibility of handling and caring for these patients. The process of allocating resources is such that patients enter the symptoms of the disease and information related to their place of residence and health status by referring to the system, and the system uses fuzzy inference and based on the symptoms to diagnose that they are infected (not infected) with covid-۱۹. Fuzzy inference subsystem uses symptoms of fever, dry cough, sense of smell, history of underlying diseases and the number of days of symptoms of disease in a person and by using membership functions for these symptoms, infers whether or not the person is sick. If the disease is diagnosed by the inference subsystem, the system selects the nearest treatment center using the geographical coordinates of the person (longitude and latitude) as well as the geographic coordinates of the medical centers in the system. Then the sick person is directed to the nearest treatment center and the necessary resources are allocated to start the process of treatment and quarantine of the patient. The selected data set for the evaluation of this system is obtained from refining the physical condition of ۶۰ people. In this thesis, the recall criterion or the obtained sensitivity is ۸۳.۳۴% and the specificity criterion is ۸۵%. According to the criteria obtained, if all people present in a region enter their information correctly into the system, the number of unnecessary visits to medical centers can be reduced. Reducing unnecessary visits to medical centers reduces financial, human and time costs in the process of treating this disease.