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Aiming at the high proportion of chronic kidney disease in the world, the irreversible development of the disease and the easy deterioration of the disease, an auxiliary diagnosis system for chronic kidney disease was designed. The classification function of random forest algorithm of data mining is used to process the patient"s laboratory data to determine whether the patient has chronic kidney disease. A B/S-based assistant diagnosis system for chronic nephropathy is designed and developed. The system integrates assistant diagnosis, diagnosis information viewing and user management of chronic nephropathy. The system is used to provide diagnostic reference for inexperienced doctors, help them improve the level of diagnosis, reduce the rate of misdiagnosis, so that patients with chronic kidney disease can be treated correctly as soon as possible, and avoid the serious consequences of delayed treatment.