Computing Missing Values Using Neural Networks in Medical Field

Data science is nowadays more and more used in many fields from industry to medicine. The main condition for application data mining methods is to have clean and consistent data sets. Often it is difficult to acquire this kind of data straight out of the process (RAW data). These data can suffer from various errors. This paper aims to evaluate novel approach to dealing with one of these errors, which is missing values of data parameters in some data records. For the purpose of this article, we have evaluated the reliability of neural networks for interpolation of missing data medical dataset.