DIABETES PREDICTION USING MACHINE LEARNING ALGORITHMS

Diabetes mellitus is a disease in which blood sugars level is abnormally high due to inability of the body to produce or respond normally to insulin. It is among the critical disease and lots of people are suffering from this disease. Due to age, lack of exercise, hereditary diabetes, bad diet, high blood pressure etc. can cause this disease. Healthcare Industries have large volume of databases so by Big Data Analytics we can extract meaningful insights such as hidden patterns, unknown correlations to discover knowledge from the data and predict the outcome accordingly. In this paper we have proposed a diabetes prediction model using Machine Learning algorithm for better classification prediction. We have tried different Machine Learning algorithms to find which gives the better accuracy of classification.

Renal response of roosters with diabetes insipidus to infusions of arginine vasotocin

In a strain of white Leghorn chicken with symptoms of hereditary diabetes insipidus (DI) and with elevated circulating levels of the antidiuretic hormone arginine vasotocin (AVT), we investigated whether the defect is based on nonfunctional endogenous AVT or on a diminished renal response to AVT. DI chickens responded to hyposmotic infusions with a higher urine flow and lower glomerular filtration rate (GFR) than healthy control birds. Urine osmolality, fractional excretion, and clearance of sodium were lower in DI birds while potassium values were similar in both groups. Hence, the high urine flow rates of the DI birds were predominantly based on a water diuresis. When infused with AVT, the GFR and the urine flow of the control birds decreased and urine osmolality increased, showing both glomerular and tubular effects of AVT. During AVT infusion, the GFR of DI birds increased, urine flow decreased only moderately, and urine osmolality was half that of the control birds. In control birds, the clearance of sodium was unchanged, whereas that of potassium decreased. In DI birds, which experienced a strong natriuresis, the clearance of both sodium and potassium increased. These data suggest that the sensitivity of the DI birds to AVT is reduced at the tubular level. The AVT-induced increase in GFR may be related to vascular effects of high AVT doses, added to the already high basal AVT level of the DI birds, in combination with an imbalance in the function of V1 and V2 receptor subtypes in these chickens.