  The percentage of patients hospitalized due to hyponatremia is getting
higher. Hyponatremia is the deficiency of sodium electrolyte in the human
serum. This deficiency might indulge adverse effects and also associated with
longer hospital stay or mortality, if it wasnt actively treated and managed.
This work predicts the futuristic sodium levels of patients based on their
history of health problems using multilayer perceptron and multivariate linear
regression algorithm. This work analyses the patients age, information about
other disease such as diabetes, pneumonia, liver-disease, malignancy,
pulmonary, sepsis, SIADH, and sodium level of the patient during admission to
the hospital. The results of the proposed MLP algorithm is compared with MLR
algorithm based results. The MLP prediction results generates 23-72 of higher
prediction results than MLR algorithm. Thus, proposed MLR algorithm has
produced 57.1 of reduced mean squared error rate than the MLR results on
predicting future sodium ranges of patients. Further, proposed MLR algorithm
produces 27-50 of higher prediction precision rate.
