Armaganov Artashes Georgievich

Clinical decision support systems (CDSS) are actively being implemented in the digital support of medical organizations, providing doctors with prompt ac cess to scientifi c and methodological evidence-based knowledge and medical data at all stages of medical care. The experience of using CDSS has shown improved patient treatment outcomes, reduced the number of medical errors, and increased clinical and cost-effectiveness in general. The study of the potential capabilities of the CDSS continues and the prospects for future developments in this area are being determined. At the same time, there are a number of problems related to the implementation of the CDSS, of which the problems of medical data security, system integration and approval of the soft ware product by medical specialists remain the most priority. CDSS have demonstrated significant potential, but their implementation and optimization remain challenging. Th e article provides an overview of research publications on the development and implementation of CDSS in medicine, the role of artificial intelligence (AI) and machine learning (ML) in the development of new models. Decision support systems for medical professionals and patients are among the priorities of applied scientific research in the interests of medicine and healthcare proposed by the Russian Ministry of Health. These types of developments are included in the section of innovative technologies in the field of digital management in the healthcare sector.