(untitled) (INTERNATIONAL CONFERENCE ON MEDICINE, SCIENCE, AND EDUCATION, 2026)
This article examines the application of Artificial Intelligence (AI) technologies in the field of medicine and analyzes their role in diagnosis, treatment, and prevention within modern healthcare systems. In recent years, systems based on Artificial intelligence have significantly transformed clinical practice by enabling early disease detection, automated analysis of medical images, optimization of clinical decision-making processes, and the development of personalized treatment strategies. Machine Learning and Deep Learning algorithms are increasingly used to analyze medical imaging data such as X-rays, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI), improving diagnostic accuracy and reducing human error. AI-powered systems support physicians in identifying patterns that may not be easily detectable through traditional diagnostic methods. The article also discusses the integration of AI into telemedicine platforms, electronic health record systems, robotic surgery, and Big Data analytics. In particular, robotic-assisted surgical technologies such as the Da Vinci Surgical System demonstrate how AI-enhanced precision can improve surgical outcomes, reduce complications, and shorten patient recovery time. The findings suggest that Artificial Intelligence enhances healthcare efficiency, increases diagnostic precision, and supports evidence-based medical decision-making. However, challenges such as data privacy concerns, high implementation costs, ethical considerations, and technical limitations remain significant issues.