Fuzzy-based artificial intelligence approach for diagnosing and recommending drugs of various kidney diseases

The Kidney is known as one of the vital organs of the human. Nowadays, due to the increase in population and unhealthy lifestyles, there have been several types of kidney diseases, namely Chronic Kidney Diseases (CKD), kidney cancer, and so on. The diseases can cause various severe effects, even the death of sufferers. Since different disease often has other symptoms, the proper diagnosis based on the patient’s existing clinical symptoms is essential. The classical problem is the limited number of specialists who can accurately diagnose and provide treatment. One of the efforts is to utilize technology as a medical expert system. Moreover, detecting kidney disease in the early stages often comprises imprecision, and a fuzzy inference system is suggested to overcome this issue. This research paper proposes designing and developing a fuzzy expert system (FES) to diagnose kidney disease based on the patient’s conditions. It adopts the fuzziness (rules, symptom weights, and severity) based on the pieces of knowledge from specialist doctors. We have conducted some experiments by using patient data from the hospital and compared the results with those of experts. It shows that this system succeeds in all tests. It is observed that this system succeeds in all tests. Thus, this system supports doctors in diagnosing the type of kidney disease among patients.