Artificial intelligence (AI) is no longer confined to the realm of science fiction; it has become an integral part of many fields, including healthcare. This article provides a concise overview of AI's history, operating principles, and specific applications in medicine, particularly in imaging techniques, medical documentation analysis, and clinical decision support. Although AI offers numerous benefits, such as faster diagnosis and improved predictive accuracy, its use faces significant challenges, including the potential for errors, ethical dilemmas, and the risk of misuse. Successful implementation hinges on rigorous validation, transparency, and integration with expert clinical judgment. Future developments will likely focus on improving algorithm accuracy, strengthening resilience against bias, and ensuring the safe application of AI for patient benefit - all through multidisciplinary collaboration. Keywords: artificial intelligence, machine learning, deep learning, neural networks, healthcare, diagnosis, imaging techniques, data analysis, clinical decision-making, AI ethics, safety, medical informatics.

Department of Infectious Diseases and Travel Medicine 2nd Faculty of Medicine Charles University and University Hospital Motol Czech Republic e mail