Missing value imputation with linear methods in the database of cardiological patients in prediction of mortality

Abstract

This study examines missing value imputation in the Russian Acute Coronary Syndrome Registry (RusACSR) and assessment of the probability of predicting mortality. Linear methods with the most probable or average value were used for imputation. The prediction problem was solved using the k-nearest neighbors method. This work reveals that the imputation method, despite their simplicity, increases the probability of prediction of mortality by 6%.