Developing a taxonomy of decisions based on artificial intelligence technologies in health care practices

Abstract

Aim. To conduct an analysis of research on the application of artificial intelligence (AI) technologies in medicine, norms and practices governing this field, and on its basis to build a taxonomy of AI-based decisions in the practice of medical services.Objectives. To structure existing AI-based solutions in medicine; to identify, based on research and state registration data, the most mature areas of AI application and potential areas of development; to study the specific features of the applied technologies.Methods. The authors using general methods of scientific cognition in various aspects considered the sphere of application of AI technologies in medicine, identified and systematized the characteristic features of the current state of this field and trends of further development.Results. According to the results of the analysis of existing solutions in the field of AI application in medicine all solutions are divided by the degree of elaboration, main processes and type of used data. The constructed taxonomy is the first step in comprehending and structuring the existing AI solutions, possibilities of their use in the process of rendering various medical services.Conclusions. Today, the most developed area of AI use in medicine is the analysis of medical images in the process of diagnosis, treatment and rehabilitation. Further development and introduction of these technologies into medical practice requires a more structured approach to assessing their effectiveness and efficiency, as well as solving a number of ethical and regulatory issues.