Machine learning in the analysis of medical data

Abstract

The article is devoted to the using of machine learning algorithms for the diagnosis of human diseases on the basis of General blood analysis. The value of this research is in the strategy of the development of the information society in the Russian Federation during 2017 - 2030. The author has developed a model that will allow us to diagnose certain chronic obstructive pulmonary diseases or allergic rhinitis with a sufficient degree of probability. This model will also allow to make a conclusion about the absence of diseases in humans. To implement the methods of machine learning to solve problems in the context of the research topic, the authors obtained impersonal data of the results of a General blood test of more than a thousand people in the city of Bryansk. The results of the study can be the basis for the development of a module which help us to support medical decision-making medical information system.