Abstract

Background. In the modern world, the role of artificial intelligence in healthcare is becoming increasingly significant, providing new opportunities to transform traditional methods of diagnosis, treatment and medical data management. This technological breakthrough not only improves the efficiency of medical procedures, but also opens up new per-spectives in the prevention and treatment of diseases. The aim. To emphasize the need to create a personalized health model using artificial intelligence to help an individual achieve and maintain optimal health and well-being. In the field of personalized treatment, artificial intelligence plays an important role, taking into account the unique characteristics of each patient. Algorithms analyze genetic information, medical history and responses to previous therapies to develop optimal treatment plans. This opens the way to individualized medicine, where the approach to each patient is based on his or her unique characteristics. Despite all the positive aspects, the introduction of artificial intelligence in healthcare also raises questions of data privacy, ethical issues and technology security. However, if these issues are resolved, artificial intelligence promises to significantly improve the quality and accessibility of medical treatment, opening new horizons in healthcare. Results. In this article, we describe breakthroughs in artificial intelligence technologies and biomedical applications, identify problems of using and further development in medical artificial intelligence systems and summarize the economic, legal and social consequences of using artificial intelligence in healthcare, and propose a scheme for constructing a model of individual human health using artificial intelligence. Conclusion. The results of the analysis of modern scientific literature allow us to draw a conclusion about the potential for creating more effective and personalized approaches to the problem of individual health using integrated artificial intelligence technologies. The proposed methodology can serve as the basis for the development of innovative deci-sion support systems in medicine and improving the quality of medical care.

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