THE ROLE AND PROSPECTS OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN MODERN MEDICINE

Abstract

Artificial Intelligence (AI) is profoundly transforming modern medicine by reshaping diagnostic processes, treatment planning, and clinical decision-making. The ability to rapidly and accurately analyze large volumes of medical data has made AI technologies an integral component of healthcare systems. With the advancement of machine learning and deep learning models, opportunities have expanded for early disease detection, the development of individualized treatment strategies, and the automation of clinical workflows.

AI technologies significantly enhance the precision and efficiency of clinical decision-making, reduce diagnostic errors, and play a crucial role in designing personalized and adaptive therapeutic strategies. Approaches such as machine learning, deep learning, and natural language processing enable healthcare professionals to systematically analyze vast amounts of patient data, identify complex and hidden patterns, and generate evidence-based predictions. Radiology, pathology, cardiology, and oncology are among the medical fields that derive the greatest benefit from the clinical application of AI technologies.

This article examines the theoretical foundations of artificial intelligence, the application of machine learning and deep learning models in medicine, and their importance in diagnostics, medical image analysis, and clinical decision support systems. Furthermore, it highlights the role and future prospects of Explainable AI, Federated Learning, and multimodal approaches in clinical practice.

The relevance of this study lies in its scientific evaluation of the real-world integration of AI technologies into medicine, assessing their advantages and existing limitations, while outlining potential directions for future development.