FUNCTIONAL CAPABILITIES OF MEDICAL ARTIFICIAL INTELLIGENCE FOR HEALTHCARE AND PROFESSIONAL EDUCATION

Abstract

Background. Practical aspects of the application of medical artificial intelligence (AI) aimed at improving clinical practice and the process of training physicians in digital technologies are of critical importance. Medical AI not only expands the capabilities of modern medicine but also establishes new standards for diagnostics, treatment, and education in healthcare. Its application spans all stages of medical care delivery – from initial diagnostics to long-term monitoring of chronic conditions.
Materials and Methods. The results of the study were systematized using scientific publication databases such as PubMed, Scopus, Web of Science, EMBASE, ERIC, IEEE Xplore, Semantic Scholar, and ScienceDirect. Bibliographic search methods, information structuring, and systems analysis were utilized at various stages of the research. The study focused on practical applications of medical AI, highlighting Google Health solutions, including specialized AI models such as Med- PaLM and Med-Gemini for healthcare tasks, as well as the DeepMind Health tool for medical imaging analysis. Expert systems like IBM Watson, UpToDate, and Epocrates, which can be integrated into electronic health records (EHR), were also analyzed.
Results. The functional capabilities of Google Health components were analyzed, including Med- PaLM, designed for natural language processing and text data analysis (e.g., EHRs, clinical protocols, and scientific articles), and the multimodal Med-Gemini model, which performs analysis of textual, visual, and signal-based medical data, risk prediction, and diagnostic support. The study highlighted Med-Gemini’s high efficiency in automating medical image analysis, processing clinical queries, predicting disease risks, and generating medical reports with expert assessment. A classification of prompt types in clinical practice and examples of their use with Med-Gemini were provided. It was substantiated that modern AI technologies can not only enhance existing expert systems but also integrate them into EHRs, creating a unified ecosystem for clinical decision support. The role of intelligent robotics with AI algorithms in introducing innovative approaches to surgery, rehabilitation, and patient care was emphasized.
Conclusions. The results of the study confirm that medical AI is a powerful tool capable of significantly improving the quality of medical care while also enhancing the professional training of medical specialists.