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Using Markov Chain to Predict by the Natural Progression of Diabetic Nephropathy at Diabetes and Endocrinology Hospital


Mohammedelameen Eissa Qurashi, Abdellateef Khalifa Hamid and Mubarak H.Elhafian


Vol. 19  No. 10  pp. 153-157


The study deals with one techniques of the stochastic process types called Markov chains in estimating movement of diabetic nephropathy patients in type1 and type2 diabetes for three years from 2015 to 2017 for the stages of diabetic nephropathy (patients pass protein in their urine after intense physical activity, patients would have advanced condition of proteinuria, Patients are suffer from severe form of edema, Hypertension and their condition is not sensitive to diuretics, It is called renal failure uremia and patient’s condition is critical) in Diabetes and Endocrinology Hospital to predict by the natural progression of Diabetic Nephropathy. The most important results movements of Diabetic Nephropathy patients represent Markov chains there is a relationship between duration of infection with diabetes and diabetes kidney disease, for a long time period diabetic nephropathy patients can be infection by the renal failure, or damage kidney disease.


Stationary distribution, Transition probability matrix, Diabetic nephropathy, Markov Chains.