Providing a Data Mining Method to Reduce the Effects of Kidney Damage on Dialysis Patients

Diabetes is a metabolic disorder that breaks down much of the food it ingests to glucose. Glucose is the main source of fuel in the body. After digestion, glucose enters the bloodstream, where it is used by the cells to growth and energy. Insulin should be presented for glucose to enter the cells. Insulin is a hormone produced by the pancreas. Food planning for diabetes and nutrition for people with diabetes should be in a manner that maintains the blood glucose levels in the normal range of all groups of foods. In this study, data mining is a nutrition program that is proportional to the amount of material in the body and food. Firstly, patients with high blood sugar are identified from experiments that are available in the database, and then test fields such as height, weight, age, urea, creatinine and blood glucose, etc. that are key elements should be extracted and integrated because patients have been tested at different times. Now, the micro-properties such as protein, carbohydrate, potassium, phosphorus, potassium, sodium, etc. as well as vitamins of fruits should be extracted and brought to the database table. In the end, using data mining based on the patients' table of tests and the table of properties of the fruit and a diet based on the nutritional formula is given to a diabetic person for a specific period. After completion of the prescribed period, the patient was tested again for improvement in the rate of kidney degradation for pre-dialysis patients as well as the lower number of referral patients for dialysis in hemodialysis and peritoneal patients. Given that the number of toxins that are applied to kill healthy kidneys by data mining have been controlled by food sources and patient tests, the regime preserves the health of the nephron by data mining and decreases the kidney degradation process.