Methodological problems of big data and artificial intelligence in the medical specialists training

The emergence of big data and artificial intelligence firstly in healthcare has caused considerable excitement, stating the need to improve approaches to diagnosis, prognosis, and treatment. Despite enthusiasm, the methodological assumptions underlying the movement of big data and artificial intelligence in medicine are rarely studied. This article outlines the methodological problems facing this movement. In particular, the following topics were considered: the theory of large data congestion, the limits of the algorithms action, and the phenomenology of the disease. These methodological issues demonstrate several important roles for these technologies that must be considered and studied before they are integrated into the healthcare system.