[Methods of artificial intelligence and their application in imaging diagnostics]

Artificial intelligence is a dynamically evolving methodology and, due to its large number of methods, its appearance becomes more important not only in industry but also in all disciplines. Diagnostic instrument manufacturers have realized relatively quickly that these types of algorithms can achieve quality improvements and reduce measurement time, which can provide them with a market advantage and more efficient patient care. In this summary, following a methodological overview, we show examples of new applications in the field of medical imaging and image processing. The analysis of the publications also confirmed the often-stated assumption made by experts that machine learning can only be applied and developed with sufficient quantity and quality of data. Such data can only be aggregated with projects that provide data warehouses that meet the technological needs of the 21st century. With this kind of integration of artificial intelligence in Big Data's methodology, regularly hidden clinical data can become accessible to advanced data science tools. This opportunity, together with relevant clinical issues, will be the basis for new R&D projects.