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This article is devoted to the theoretical study of the foundations of the effective operation of the company’s structural divisions. It examines the general directions of development of companies and the main strategies that are most relevant for companies that produce goods in modern market conditions. Also, in this article, attention is paid to specific areas of improvement of divisions in companies, the main of which are precisely the production departments. To understand the essence of unit improvement, leadership strategies were considered. Methods and factors influencing the improvement of the activity of a subdivision of a manufacturing enterprise are analyzed. All factors are considered in the context of the enterprise from two sides, both external and internal, and diagrams are built for them for visual presentation. On the basis of these factors, directions were developed to increase the economic efficiency of activities. The final stage was considered 8 ways to improve the efficiency of enterprise management. At the end of the work, conclusions were drawn about the reasons that necessitate the improvement of units in the modern market. The purpose of this work is to study the main directions for the development of companies and the activities of their structural divisions.

This article explores the use of artificial intelligence in medicine, in particular in radiology, pathology, drug development. The usefulness of robotic assistants in the medical field is revealed, including machine learning in medical science, as well as routing in hospitals. It also discusses such machine learning methods as classification methods, regression restoration methods, clustering methods. As a result, based on what is considered in this article, it is concluded that manual processing becomes more complicated and impossible with a large amount of data. There is a need for automatic processing that can transform modern medicine. And also, conclusions were made about how accurately the deep learning mechanisms can provide a more accurate result in the processing and classification of images compared to the results obtained at the human level. It became clear that deep learning not only aids in the selection and extraction of characteristics, but also has the potential to measure predictive target audiences and provide proactive predictions to help clinicians go a long way.