One of the most promising areas of health innovation is the application of artificial intelligence (AI), primarily in radiology for medical imaging. This thesis provides basic definitions of terms “machine learning” „deep learning“ and analyses the integration of AI into radiology. Publications on AI have drastically increased in last five years. In this paper we deal with the topic of artificial intelligence and its application in radiology, radiography and other fields. In the world of large data and flood of information, systems that apply artificial intelligence become more and more important. Different methods of artificial intelligence are described. They include machine learning, artificial neural networks, deep learning. Artificial intelligence systems should be oriented to mankind in the service of the general good, improving human well-being, respecting laws and eithic norms. Artificial intelligence involves processes of reasoning, knowledge, automated planning, learning, processing, perception, manipulation of data, so it has undoubtedly found its place in radiography. The literature has been reviewed and articles have been identified for the application of artificial intelligence in areas of x-rays, especially mammography, ultrasound, application to Computed Aided Detection (CAD), CT, MRI and other fields where diagnostic radiological modalities of imaging are used. One of the most promising areas of innovation in healthcare is the use of artificial intelligence (UI), primarily in radiology.