THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN MEDICINE

Abstract

Artificial intelligence (AI) has become an important technological component of modern medicine, particularly in medical imaging, clinical decision support, electronic health record analysis, pathology, personalized medicine, drug development, and healthcare administration. Machine learning and deep learning methods can identify complex patterns in large datasets that may be difficult to recognize through conventional analytical approaches. Research published in leading medical journals has demonstrated that AI systems can achieve high levels of diagnostic performance in selected tasks, including skin-cancer classification and mammographic assessment. At the same time, the clinical value of AI cannot be determined solely by algorithmic accuracy. Generalizability, external validation, data quality, algorithmic bias, explainability, privacy, cybersecurity, regulatory oversight, and the interaction between clinicians and AI systems are critical determinants of safe implementation. The World Health Organization has emphasized that AI in health should be developed and deployed according to principles of human autonomy, safety, transparency, accountability, inclusiveness, equity, and sustainability. Recent reporting frameworks, including CONSORT-AI, DECIDE-AI, and TRIPOD+AI, have strengthened methodological standards for evaluating AI-based clinical technologies. Regulatory developments also demonstrate the increasing integration of AI into medical-device development. The present article reviews the evidence concerning the role of AI in modern medicine and analyzes its principal opportunities and limitations. The evidence indicates that AI is most appropriately regarded not as a replacement for physicians, but as a technological instrument capable of augmenting clinical decision-making, improving workflow, supporting early detection, and facilitating more data-driven healthcare when appropriately validated and governed.