Modern medicine is on the threshold of a technological transformation caused by the active introduction of artificial intelligence into clinical practice. These technologies not only speed up diagnostics and improve the accuracy of surgical interventions, but also enable the creation of individualized treatment plans, the development of new drugs, and remote access to medical services. The relevance of this research is determined by the growing role of artificial intelligence in healthcare and the need to systematize its existing applications. This article provides a comprehensive analysis of the application of artificial intelligence technologies in modern medicine. The article systematizes the application of AI, examines key examples of projects operating in Russia, and outlines the prospects for technology development over the next 5-10 years. Particular attention is paid to the ethical, legal, and organizational challenges associated with the implementation of AI in medical practice.

Keywords: artificial intelligence, medicine, telemedicine

Modern telemedicine is developing unevenly across the globe, and there are objective reasons for this. This article analyzes modern information and computing systems and technologies used for diagnosing and treating patients. This article provides a brief history of telemedicine as a technical means of providing medical care and provides examples of the use of information technology in Russian and global medical practice. Key approaches to the use of large-scale language models as a technological core to assist healthcare professionals in making professional decisions are explored. Examples of optimization of diagnostic and treatment processes using digital technologies are analyzed. The author attempts to analyze the latest scientific achievements in the use of information technologies in medicine, with the aim of demonstrating the transition to a new level of quality of medical services through the use of information and computing systems.

Keywords: telemedicine, digital technologies, large language models, medical diagnostics, medical practice, technology analysis, history of telemedicine, comparative analysis, digital transformation, systems analysis

The article proposes a new technique for automating the screening of radiation diagnostics of employees of enterprises using elements to support medical decision-making, in particular, the U-shaped architecture of a convolutional neural network with a dual attention mechanism. A special feature of the architecture is the use of an attention mechanism based on "compression and excitation" blocks, which makes it possible to improve the quality and accuracy of digital medical data analysis, taking into account the features of computed tomography images.

Keywords: machine learning, convolutional neural network, computed tomography, architecture, chronic obstructive pulmonary disease